Professor Gabriel Lodewijks

Remote vehicle operators (RVO) work in a sensory-deprived environment. A reduction or absence of sensory cueing like auditory feedback, combined with variable workload, has been attributed to a number of remotely piloted aircraft (RPA) accidents. Therefore, this research sought to understand the relationship between workload and dynamic auditory feedback on RVO task performance. Twenty-four participants completed a counterbalanced series of decision-making (spatial orientation accuracy) and perception (spotting accuracy) tasks in an automated beyond visual line of sight environment, under varying workload and auditory volume levels. The management style employed by participants in dealing with the auditory information was also measured and compared with decision-making performance. A relative decline in spatial orientation accuracy was evident when auditory feedback was considered ¿soft¿ or ¿loud¿ (±10 dBA) compared with a participant-defined comfortable volume level, but contingent on an adequate level of workload experienced concurrently. From an applied perspective, these findings support the inclusion of adaptive auditory systems in future Remotely Piloted Aircraft Systems (RPAS) designs.

Absent or reduced sensory cueing can deprive pilots operating remotely piloted aircraft beyond visual line of sight (BVLOS) of vital information necessary for safe flight. The present study tested the effects of real-time auditory feedback on remote pilot perception and decision-making task performance in an automated BVLOS flight, under three levels of workload (Low, Moderate and High). Results from 36 participants revealed workload and auditory feedback influenced perception task performance in terms of error type count, with misses more frequent than wrong identifications. In terms of performance in the decision-making task, under low and moderate levels of workload, auditory feedback was found to improve performance. Conversely, under high workloads, an inflexion or tipping point occurred whereby auditory feedback became detrimental to task performance. These results correspond with the expected behavioural responses to external stressors as predicted by the Arousal and Maximal Adaptability theory, and build upon previous findings related to workload, auditory feedback and remote pilot task performance. Practitioner summary: This study tested the effect of real-time auditory feedback and dynamic workloads on remote pilots¿ task performance. Auditory feedback and workload each influenced the perception tasks in terms of error types committed. Auditory feedback improved decision-making task performance under low and moderate workloads, and reduced performance under high workloads. These results may benefit practitioners by considering the nuanced effects of auditory feedback on human task performance within sensory deprived working environments, including those utilising teleoperated systems.

This study examines the service network design problem (SNDP) for passenger shuttle buses in the airport and nearby places (e.g. train stations, parking, hotels, shopping areas). A time¿space service network for bus flows and time¿space networks for passenger flows are developed. Based on proposed time¿space networks, the studied SNDP is formulated as a mixed integer linear program (MILP) for a single-type bus fleet and deterministic passenger demand, where the objective is to minimize the weighted sum of passenger cost and service operating cost. We then extend the developed SNDP model to the heterogeneous multi-type bus fleet case and the stochastic demand case. To solve the stochastic demand case, a Monte Carlo simulation-based approach is adopted, which is further coupled with the ¿effective demand¿ concept (mean demand value plus a margin). The proposed SNDP models and solution approach are applied on the inter-terminal transport network at Sydney Kingsford Smith Airport for illustration.

Nowadays, more automated or robotic twin-crane systems (RTCSs) are employed in ports and factories to improve material handling efficiency. In a twin-crane system, cranes must travel with a minimum safety distance between them to prevent interference. The crane trajectory prediction is critical to interference handling and crane scheduling. Current trajectory predictions lack accuracy because many details are simplified. To enhance accuracy and lessen the trajectory prediction time, a trajectory prediction approach with details (crane acceleration/deceleration, different crane velocities when loading/unloading, and trolley movement) is proposed in this paper. Simulations on different details and their combinations are conducted on a container terminal case study. According to the simulation results, the accuracy of the trajectory prediction can be improved by 20%. The proposed trajectory prediction approach is helpful for building a digital twin of RTCSs and enhancing crane scheduling.

Purpose ¿ Current literature presents limited measurement methods of quantifying manufacturers¿ performance with environmental concerns. The purpose of this paper is to construct a company performance index for benchmarking motor vehicle manufacturers (MVMs) with environmental concerns. Design/methodology/approach ¿ Methods of constructing the index include regression analysis, a modified linear method for normalizing variables and a geometric mean for aggregating variables into a single index IMVM (index for MVMs). A case study is conducted in 12 MVMs from 2008 to 2017. A sensitivity analysis with the simple additive weighting method is performed to analyze how different aggregation methods affect the final value. The index IMVM is assessed through a benchmark with three existing indices. Findings ¿ Three realistic considerations are identified from MVMs, based on which proper and transparent methods are chosen to construct the IMVM. The construction of the index IMVM has been assessed through a benchmark against the methodologies of three other indices. The results indicate that the new measurement is feasible and effective for MVMs to measure their company performance from an environmental perspective. Practical implications ¿ The construction of the index IMVM can support policymakers with accurate statistics for decision-making. As a response to current imperative climate policies, this paper raises awareness of CO2 emissions in vehicles¿ production. For statistical organizations and stakeholders in the investment world, this paper provides available and reliable statistics for trend analysis of different MVMs. Originality/value ¿ A new method is designed for constructing a company performance index for MVMs. Three environmental variables are identified based on literature, their environmental impact as well as their data availability from public documents. A ranking by manufacturer with environmental concerns is generated. This index can contribute with available statistics and useful insights toward decision-making.

Composite indicators (CIs) are needed for decision makers to effectively benchmark holistic company performance. Composite indicators at macro levels are inappropriate to be implemented at the company level. By a literature survey, this article identified 29 individual methods for constructing CIs, 17 specific business sectors where CIs have been utilized in practice, and the motor vehicle manufacturing sector as the most studied sector. This article identified nine problems and provided four recommendations for future research.

A robotic mobile fulfillment system (RMFS) is a ¿parts-to-picker¿ system employing a fleet of autonomous vehicles (AV), which transport pods between a storage area and picking stations. In this paper, an AV interference-free scheduling on bidirectional paths (IFSB) approach is studied and shows better working efficiency than unidirectional paths. In order to model AV scheduling on bidirectional path with interference-free constraints, a no-wait flexible process job shop scheduling problem (NWFPJSP) is employed to evaluate total completion time. A mathematical model aiming to minimize the total completion time is presented with as constraint interference-free operation. An A* algorithm is modified for path planning and a simulated annealing algorithm (SA) is employed for scheduling AVs and their paths. Based on a case study with a small RMFS, the IFSB approach results in a 40% increase of the storage capacity and a 22% decrease of the total completion time when compared to a unidirectional approach. Meanwhile, the number of AVs stop-starts are decreased by 40% and the paths length for all AV are decreased by 36%. This indicates the great potential of bidirectional paths in future logistic applications, which may increase the storage capacity, working efficiency, technical health of the AVs, and environmental sustainability.

Mental fatigue has been lacked attention in developing eye-tracking fatigue detection system for drivers. However, it has great influence on eye movement which could account for the poor validity of current fatigue detectors only focusing on sleep-related fatigue. This work sought to investigate the influence of two types of task-related mental fatigue on eye movement by examining 8 saccade-based, 3 blink-based, and 1 pupil-based metrics. We propose that two types of task-related fatigue caused by cognitive overload and prolonged underload will induce different physiological responses to eye-motion features. Twenty participants completed a vigilance task before and after a 1-h driving with a secondary task in a virtual simulation environment, while forty participants, divided equally into two groups, finished the same task before and after a 1-h and 1.5-h monotonous driving. T-test was applied to analyse the eye-motion, subjective and vigilance data during vigilance task. We found that overload driving made drivers vigilance ability decrease. The eye metrics showed different changes in underload and overload scenario. The blink duration, the mean velocity of saccade and saccade duration increased after 1-h overload driving, while the pupil diameter decreased. However, none of those changes were observed in 1.5-h underload driving, but saccade duration had a significant increase. The fatigue response to heavy demands over short periods of driving is different from the lighter demands over long periods in terms of eye-motion metrics. Considering mental fatigue in designing an eye-tracking fatigue detection system could possibly improve its accuracy.

Optimizing the design of an airport baggage handling transport system (BHTS) with respect to the minimization of the total costs and energy consumption is essential to reduce costs and Carbon dioxide (chemical formula CO2) emissions in airport operations. This paper introduces a mathematical model that comprehensively considers relevant costs regarding the operation of belt conveyors in a BHTS. Specifically, the Capital Expenditure (CapEx) and Operational Expenditure (OpEx) are considered in the airport BHTS cost function. Furthermore, to include the impact of CO2 emissions, the offsetting costs of CO2 emissions are included in the airport BHTS cost function. This function forms the basis of an objective function that can be used to optimize the airport BHTS's design by metaheuristic algorithms. Three state-of-the-art particle swarm optimization (PSO) algorithms are utilized to solve the airport BHTS optimization problem. The results of experiments show that the three PSO variants can solve the optimization problem effectively and efficiently. The self-regulation PSO algorithm performed the best in terms of CPU time and has been used for the case studies. Extensive tests of the impact of key parameters, e.g., capacity and system length, on the optimized solutions have been conducted. Experiments show that a system with several belt conveyors of shorter lengths performs better than a system with one long conveyor. In reality however, more parameters play a role like the varying baggage throughput per hour and therefore the BHTS problem needs to be optimized case-by-case. Optimizing an airport BHTS design leads to a significant reduction in CO2 emission and thus costs.

Abstract: On the basis of the influence of dry season on ship traffic flow, the gathering and dissipating process of ship traffic flow was researched with Greenshields linear flow¿density relationship model, the intrinsic relationship between the ship traffic congestion state and traffic wave in the unclosed restricted channel segment was emphatically explored when the ship traffic flow in a tributary channel inflows, and the influence law of multiple traffic waves on the ship traffic flow characteristics in unclosed restricted segment is revealed. On this basis, the expressions of traffic wave speed and direction, dissipation time of queued ships and the number of ships affected were provided, and combined with Monte Carlo method, the ship traffic flow simulation model in the restricted channel segment was built. The simulation results show that in closed restricted channel segment the dissipation time of ships queued is mainly related to the ship traffic flow rate of segments A and C, and the total number of ships affected to the ship traffic flow rate of segment A. And in unclosed restricted channel segment, the dissipation time and the total number of ships affected are also determined by the meeting time of the traffic waves in addition to the ship traffic flow rate of segments. The research results can provide the theoretical support for further studying the ship traffic flow in unclosed restricted channel segment with multiple tributaries Article Highlights: 1.The inflow of tributaries' ship traffic flows has an obvious impact on the traffic conditions in the unenclosed restrictedchannel segment.2.The interaction and influence between multiple ship traffic waves and the mechanism of generating new traffic waves are explained.3.The expression of both dissipation time of queued ships and the total number of ships affected in the closed and unclosed restricted channel segment are given.

This paper proposed a scheme design for Sydney¿s frontport check-in system, which completes check-in and baggage drop-off at Sydney¿s Circular Quay, and transports the baggage to Sydney Kingsford Smith Airport by waterway, and provided a strengths, weaknesses, opportunities and threats (SWOT) analysis of Sydney¿s frontport check-in system. Using the process method of quality management, the frontport check-in process was divided into three sub-processes: baggage consignment, baggage packing and transportation, and airport baggage handling. The eight key elements of each sub-process such as input, output, resources, and methods, etc. were discussed, the key factors influencing the cost of baggage transportation were analyzed, and the cost control measures such as adopting economic speed, reducing fuel consumption of the main engine, improving the ship loading rate, and raising loading and unloading efficiency were proposed. At the same time, two different types of baggage transportation ships and other parameters that affect the cost such as the number of berths, ships, lifting machineries, and the yard area were analyzed and calculated through calculation cases. This scheme is a beneficial addition to the existing in-town check-in system.

The Shuttle-Based Storage and Retrieval System (SBS/RS) has been widely studied because it is currently the most efficient automated warehousing system. Most of the related existing studies are focused on the prediction and improvement of the efficiency of such a system at the design stage. Hence, the control of existing SBS/RSs has been rarely investigated. In existing SBS/RSs, some empirical rules, such as storing loads column by column, are used to control or schedule the storage process. The question is whether or not the control of the storage process in an existing system can be improved further by using a different approach. The storage process is controlled to minimize the makespan of storing a series of loads into racks. Empirical storage rules are easy to control, but they do not reach the minimum makespan. In this study, the performance of a control system that uses reinforcement learning to schedule the storage process of an SBS/RS with fixed configurations is evaluated. Specifically, a reinforcement learning algorithm called the actor-critic algorithm is used. This algorithm is made up of two neural networks and is effective in making decisions and updating itself. It can also reduce the makespan relative to the existing empirical rules used to improve system performance. Experiment results show that in an SBS/RS comprising six columns and six tiers and featuring a storage capacity of 72 loads, the actor-critic algorithm can reduce the makespan by 6.67% relative to the column-by-column storage rule. The proposed algorithm also reduces the makespan by more than 30% when the number of loads being stored is in the range of 7¿45, which is equal to 9.7%¿62.5% of the systems¿ storage capacity.

Remotely Piloted Aircraft Systems (RPAS) have facilitated new growth in civil aviation. Unlike manned aircraft, however, they are operated without auditory feedback and normally flown under two visual conditions: in direct visual-line-of-sight to the remote pilot (VLOS) and beyond VLOS with first-person-view imagery transmitted via onboard cameras (BVLOS). The present research examined the effectiveness of audiovisual cueing on remote pilot manual flying performance. Eighteen pilots (three female) completed six navigation and 12 spotting tasks. Their flying performance (horizontal accuracy, vertical accuracy and timeliness) was examined under three different visual display types (VLOS (Control), BVLOS-Monitor & BVLOS-Goggles), with and without real-time auditory feedback, and two wind component (no wind and wind) conditions. Horizontal deviation and timeliness improved in the BVLOS-Monitor condition navigation task, while auditory feedback produced nuanced examples of improved and degraded pilot performance. These results indicate how the specificity of the task, combined with different levels of audiovisual feedback influences remote pilot performance. These findings support the rationalisation for the provision of multimodal dynamic sensory cueing in future RPAS. Practitioner summary: Accuracy and timeliness of remote pilot manual flying performance was measured under a combination of audiovisual feedback in calm and wind shear conditions. The inclusion of real-time auditory feedback as an additional sensory cue is uncommon; this study demonstrated nuanced examples of improved and degraded manual flying performance. The provision of dynamic sensory cueing made available to remote pilots in future RPAS should be considered.

Introduction: Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices. Method: This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.

Belt conveyor systems are widely utilized in transportation applications. This research aims to achieve fault detection on belt conveyor idlers with an acoustic signal based method. The presented novel method uses Mel Frequency Cepstrum Coefficients and Gradient Boost Decision Tree for feature extraction and classification. Thirteen Mel Frequency Cepstrum Coefficients are extracted from acquired sound signal as features. A Gradient Boost Decision Tree model is developed and trained. After training, the model is applied to a testing dataset. Results show that the trained model can achieve diagnosis accuracy of 94.53%, as well as recall rate up to 99.7%. This study verifies the proposed method for acoustic signal based fault detection of belt conveyor idlers.

A wheel impact load detector is used to assess the condition of a railway wheel by measuring the dynamic forces generated by defects. This system normally measures the impact force at multiple points by exploiting multiple sensors to collect samples from different portions of the wheel circumference. The outputs of the sensors are used to estimate the dynamic force as the main indicator for detecting the presence of the defect. This method fails to identify the defect type and its severity. Recently, a data fusion method has been developed to reconstruct the wheel defect signal from the wheel¿rail contact signals measured by multiple wayside sensors. The reconstructed defect signal can be influenced by different parameters such as train velocity, axle load, number of sensors, and wheel diameter. This paper aims to carry out a parametric study to investigate the influence of these parameters. For this purpose, VI-Rail is used to simulate the wheel¿rail interaction and provide the required data. Then, the developed fusion method is exploited to reconstruct the defect signal from the simulated data. This study provides a detailed insight into the effects of the influential parameters by investigating the variation of the reconstructed defect signals.

This paper envisions a mixed network with autonomous vehicle (AV) expressways and non-autonomous local streets in the future, where a trip may consist of both the AV self-driving part and the manual-driving part. A linear traffic corridor approach is adopted, where AV expressways and non-autonomous streets are in parallel and are connected through the entrance/exit. This mimics the intermediate future where AV expressways may be initially deployed along major corridors. We model and analyze road users¿ route choice in such a mixed network. We also examine how AV expressways are integrated with the local streets can affect system performance.

Purpose: The purpose of this paper is to develop an approach to measuring the performance of motor vehicle manufacturers (MVMs) from economic and environmental (E&E) perspectives. Design/methodology/approach: Eight measures are identified for benchmarking the performance from E&E perspectives. A new company performance index IMVM is constructed to quantitatively generate the historical data of MVMs¿ company performance. Autoregressive integrated moving average (ARIMA) models are built to generate the forecast data of the IMVM. The minimum Akaike information criteria value is used to identify the model of the best fit. Forecast accuracy of the ARIMA models is tested by the mean absolute percentage error. Findings: The construction of the index IMVM is benchmarked against three frameworks by six benchmark metrics. The IMVM satisfies all of its applicable metrics while the three frameworks are incapable to satisfy their applicable metrics. Out of 15, 4 MVMs are excluded for benchmarking future performance due to their non-stationary time series data. Based on the forecast IMVM data, GM is the best performer among the 15 samples in the FY2018. Originality/value: This research highlights the environmental perspective during vehicles¿ production. The development of this approach is based on publicly available data and transparent about the methods it used. The data out of the approach can benefit stakeholders with insights by benchmarking the historical performance of MVMs as well as their future performance.

Purpose: The development of bulk material handling equipment can be accelerated and made less expensive when testing of virtual prototypes is adopted. However, the modelling of a grab unloader requires a large volume (77 m3) of iron ore pellets, making the computational costs prohibitive. This paper investigates the extent to which the original particles can be substituted by larger, coarser grains. It is crucial that this particle upscaling does not alter the realistic behaviour of the simulated bulk material, nor its interaction with the bulk handling equipment. Approach: First, our coarse graining technique is explained and set out for the particle system at hand. The material behaviour is then characterized using three laboratory experiments (two angle of repose tests and a penetration test). Next, the results of simulations using two contact models with and without coarse graining with different scale factors are compared with the measured material behaviour and material-equipment interaction. This includes a comparison of the macrobehaviour of the bulk material and the tool interaction of coarser grains in a cutting and sliding process. After reaching a satisfactory verified solution on the laboratory scale, the material behaviour and interaction behaviour of a large-scale experiment are modelled. A simulation model of a grab unloader was used for validation of the chosen coarse graining approach. Findings: Using the scaling method presented, the macroscopic tests indicated consistent material behaviour, regardless of the chosen particle scale for two contactmodels. Scaling of the tool interaction process produced mixed results: the sliding process scaled consistently but the penetration process did not, most likely because it is significantly harder for coarser grains to move since they have to move further to the sides before the tool can pass, leading to higher normal forces and frictional forces on the tip. This inconsistency was compensated for by adjusting the wall friction coefficient in the tip of the penetration tool. Once this adapted coarse graining scheme was applied to the industrial-scale simulation of a grab unloader, it produced consistent particle-scale invariant results. Originality/value: This research is the first to show how coarse graining schemes for DEM simulations can be applied to large-scale bulk handling equipment involving dominance of material equipment interaction through penetration of the bulk material.

Nowadays, the major ports around the world usually consist of multiple terminals and service centers which are often run by different operators. Meanwhile, inland terminals have been also developed to reduce port congestion and improve transport efficiency.The integrated planning of inter-terminal transport (ITT) between the seaport and inland terminals helps in providing frequent and profitable services, but also could lead to higher overall planning complexity. Moreover, the ITT system usually involves multiple stakeholders with different or even conflicting interests. Although an increasing number of studies have been conducted in recent years, few studies have summarized the research findings and indicated the directions for future research regarding ITT. This paper provides a systemic review of ITT planning: we examine 77 scientific journal papers to identify what kind of objectives should be achieved in ITT system planning, which actors should be involved, and what methodologies can be used to support the decision-making process. Based on the analysis of the existing research, several research gaps can be found. For example, the multi-modality ITT systems are rarely studied; cooperation frameworks are needed in the coordination of different actors and quantitative methodologies should be developed to reflect the different actors' financial interests.

Abrasive wear can cause surface damage of bulk solids handling equipment. Reducing the abrasive wear is beneficial to lower the maintenance cost. Previous research elaborated on the bionic design methodology to reduce surface wear of bulk solids handling equipment. To facilitate the application of the bionic design methodology in bulk solids handling, this research examines the effectiveness of a bionic model using discrete element method (DEM) simulations. A reference case of an abrasive wear scenario in bulk solids handling is simulated, and the wear volume of a smooth chute surface is predicted. By applying a bionic model to the chute surface and using the same simulation model, the wear volume of a bionic surface is predicted. By comparisons, it is identified that the bionic surfaces produce less wear than the smooth surface. In addition, the sensitivities of the geometrical parameters for the wear reduction are predicted. Therefore, the abrasive wear reduction effectiveness of the bionic model is demonstrated.

The ultimate strength of metallic pipelines will be inevitably affected when they have suffered from structural damage after mechanical interference. The present experiments aim to investigate the residual ultimate bending strength of metallic pipes with structural damage based on large-scale pipe tests. Artificial damage, such as a dent, metal loss, a crack, and combinations thereof, is introduced to the pipe surface in advance. Four-point bending tests are performed to investigate the structural behavior of metallic pipes in terms of bending moment-curvature diagrams, failure modes, bending capacity, and critical bending curvatures. Test results show that the occurrence of structural damage on the pipe compression side reduces the bending capacity significantly. Only a slight effect has been observed for pipes with damage on the tensile side as long as no fracture failure appears. The possible causes that have introduced experimental errors are presented and discussed. The test data obtained in this paper can be used to further quantify damage effects on bending capacity of seamless pipes with similar D/t ratios. The comparison results in this paper can facilitate the structural integrity design as well as the maintenance of damaged pipes when mechanical interference happens during the service life of pipelines.

Belt conveyor systems are widely utilized for continuous transport of bulk materials. Maintenance activities are essential to ensure the reliability of belt conveyor systems. Conventional diagnosis decision is achieved based on empirical constant thresholds. The Challenge of this study is to propose a framework of integrated maintenance decision making for belt conveyor idlers. Information from operational conditions, reliability estimation of idlers and condition monitoring data are integrated for accurate decision making. Innovatively, in the proposed framework threshold of the monitoring parameter can vary according to real time operational conditions and reliability estimation results. A simulation study is presented to demonstrate the effectiveness of framework. Simulation results show that the framework can result in more accurate maintenance decision making compared to conventional approaches.

Wheel impact load detectors are widespread railway systems used for measuring the wheel¿rail contact force. They usually measure the rail strain and convert it to force in order to detect high impact forces and corresponding detrimental wheels. The measured strain signal can also be used to identify the defect type and its severity. The strain sensors have a limited effective zone that leads to partial observation from the wheels. Therefore, wheel impact load detectors exploit multiple sensors to collect samples from different portions of the wheels. The discrete measurement by multiple sensors provides the magnitude of the force; however, it does not provide the much richer variation pattern of the contact force signal. Therefore, this paper proposes a fusion method to associate the collected samples to their positions over the wheel circumferential coordinate. This process reconstructs an informative signal from the discrete samples collected by multiple sensors. To validate the proposed method, the multiple sensors have been simulated by an ad hoc multibody dynamic software (VI-Rail), and the outputs have been fed to the fusion model. The reconstructed signal represents the contact force and consequently the wheel defect. The obtained results demonstrate considerable similarity between the contact force and the reconstructed defect signal that can be used for further defect identification.

This paper investigates the problem of inter-terminal movements of containers and vehicles within a port area in order to achieve an integrated and effective transport within the port and towards the hinterland. Containers from different port terminals are first moved to a rail yard and then delivered to the hinterland by rail. To provide insights for stakeholders such as port authority and terminal operators into tactical planning problems, e.g., the coordination between terminals, railway timetable and train sizes, this paper proposes an optimization model describing the movement of containers and various vehicles between and inside terminals. The model aims at improving the container delivery from container terminals to the hinterland considering both railway hinterland transport and terminal handling operations. A network inspired by a real-life port area and its hinterland is used as a test case to test different components, i.e., inter-terminal transport connections, train formation, railway timetable. A rolling horizon framework is used to improve the computation efficiency in large transport demand cases. The result of the optimization helps in identifying the most promising features, namely, that more connections between terminals and a flexible outbound railway timetable could contribute to improving the integrated container transport performance.

Purpose: Today, most of the car manufacturers world-wide have embraced the principles of lean manufacturing on strategic and operational level. On strategic level car companies like Toyota (Womack et al., 1990) shifted 63 per cent of the value of the car towards the first, second and third tier suppliers for the co-production and co-development of cars as an effect of lean implementation. However, lean implementation was also followed by for instance Ford and GM in the USA, the latter company faced a sudden disruption in 2009 due to the break-out of the financial crisis in 2008, while Ford survived. Could this be foreseen? The exclusive use of (classic) financial performance indicators may give a false image of a company¿s current and future performance. There is a need for a model to identify ¿the stars and the laggards¿ regarding car companies by taking into account non-financial and intangible dimensions as advocated by Neely et al. (2003) regarding the third generation of business performance measurement systems. The purpose of this paper is therefor to propose a method to measure and benchmark car company performance which includes the non-financial R&D dimension as well as supply chain, value creating and employee dimensions. These dimensions are present in the value leverage model (van Blokland et al., 2012a, 2012b) which can serve as a basis for this method. The aim is to contribute to the third generation business performance measurement systems by further development of the value leverage model towards a maturity model for benchmarking car company performance. The proposed method can provide a big picture and give insight regarding company performance and direction of the performance. Design/methodology/approach: Value leverage can be measured by a correlation analysis regarding three dimensions, namely, supply chain, R&D and value creation, all relative to the employee or capita which results in the average value leverage (AVL) factor. This AVL factor can be used to compose a combined relative and absolute ranking. The score regarding the AVL results in a relative ranking expressing the level of stability regarding the car companies value chain and system. For the absolute ranking the car companies receive per variable parameter a score according to their absolute performance relative to the other car companies. The relative and absolute ranking are presented on the vertical and horizontal axes forming a matrix. The matrix is the basis for the stability-value leverage maturity model for measuring and benchmarking company performance. With the proposed method, the following main research question can be answered: ¿How can company performance be measured and benchmarked from a stability-value leverage perspective?¿. Findings: With the proposed method, stability-value leverage performance can be measured. The relative ranking on the vertical axis and the absolute ranking form together a matrix which is presented by a scatterplot. A matrix with four maturity levels emerged from the analysis by introducing the average score of all the car companies together in the data set crossing the matrix vertical and horizontal. The four levels are as follows: Level I, low stability ¿ low value leverage; Level II, low stability ¿ high value leverage; Level III, high stability ¿ low value leverage; and Level IV, high stability ¿ high value leverage. Stability-value leverage performance of car companies can be measured over time which makes it possible to observe to which direction the car company migrates for instance from Level I to Level III, before and after the financial crises in 2008. The car companies BMW, Daimler, Audi, Ford and Honda are the best performing companies in stability-value leverage over the period 2000-2014, as they are situated at Level IV. With the findings, the main research question can be answered. The value leverage indicators can be used for measuring and benchmarking company performance regard...

Numerical investigation is conducted in this paper on both intact and dented seamless metallic pipelines (diameter-to-thickness ratio D/t around 21), deploying nonlinear finite element method (FEM). A full numerical model is developed, capable of predicting the residual ultimate strength of pipes in terms of bending capacity (Mcr) and critical curvature (¿cr). The simulation results are validated through test results by using the measured material properties and specimen geometry. An extensive parametric investigation is conducted on the influences of material anisotropy, initial imperfection, friction of the test set-up and dent parameters. It is found that the structural response is quite sensitive to the frictions that have been introduced by the test configuration. For a pipe with a considerable dent size, the effect of manufacturing induced initial imperfection is insignificant and can be neglected in the FEM simulation. The material yield stress in the pipe longitudinal direction dominates the bending capacity of structures. In the end, formulas are proposed to predict the residual ultimate strength of dented metallic pipes under pure bending moment, which can be used for practical purposes. A satisfying fit is obtained through the comparison between the formulas and FEM methods.

Belt conveyors play an important role in the dry bulk material handling process. Speed control is a promising method of reducing the power consumption of belt conveyors. However, inappropriate transient operations might cause risks like material spillage away from the belt conveyor. The unexpected risks limit the applicability of speed control. Current studies on speed control mainly focus on designing energy models of belt conveyors or building control algorithms of variable speed drives, while rare researchers take into account the risks in transient operations and the dynamic performance of belt conveyors under speed control. The paper proposes an Estimation-Calculation-Optimization (ECO) method to determine the minimum speed adjustment time to ensure healthy transient operations. The ECO method is composed of three steps and takes both risks in transient operations and the conveyor dynamics into account. In the Estimation step, an estimator is built to approximate the permitted maximum acceleration by treating the belt as a rigid body. Taking the belt's visco-elastic property into account, the Calculation step computes the conveyor dynamics by using a finite-element-method. With respect to the risks in transient operations, the Optimization step improves the conveyor's dynamic behaviors and optimizes the speed adjustment time. A case of a long belt conveyor system is studied and the ECO method is applied. The secant method is also used to improve the optimization efficiency. According to the experimental results, the ECO method is successfully used to determine the minimum speed adjustment time to ensure healthy transient operations, including both the accelerating and the decelerating operations. With the suggested adjustment time, unexpected risks are avoided and the belt conveyor shows an appropriate dynamic behavior. Accordingly, the ECO method ensures healthy transient operations and improves the applicability of speed control with the consideration of the potential risks and the conveyor dynamics.

Modern technologies have enabled approaches to estimate freshness of perishable products during production and distribution. This allows supply chains to apply more advanced decision support systems in order to further reduce the loss of perishable products. In this paper we focus on the postharvest scheduling of starch potatoes. In particular we propose a quality-aware scheduling method that can be used in a decision support system for starch potato postharvest operations. Considering the quality of stored potatoes in real-time, the method determines when and how many potatoes should be harvested, sent for starch production, or stored. A centralized and a distributed control strategy are developed, with the aim of minimizing total starch loss in dynamic environments. Simulation experiments illustrate how the proposed approaches deal with disturbances, and that the total starch loss can be reduced when real-time quality information of potatoes is taken into account.

We study the integration of real-time traffic management and train control by using mixed-integer nonlinear programming (MINLP) and mixed-integer linear programming (MILP) approaches. Three innovative integrated optimization approaches for real-time traffic management that inherently include train control are developed to deliver both a train dispatching solution (including train routes, orders, departure and arrival times at passing stations) and a train control solution (i.e., train speed trajectories). Train speed is considered variable, and the blocking time of a train on a block section dynamically depends on its real speed. To formulate the integrated problem, we first propose an MINLP problem (PNLP), which is solved by a two-level approach. This MINLP problem is then reformulated by approximating the nonlinear terms with piecewise affine functions, resulting in an MILP problem (PPWA). Moreover, we consider a preprocessing method to generate the possible speed profile options for each train on each block section, one of which is further selected by a proposed MILP problem (PTSPO) with respect to safety, capacity, and speed consistency constraints. This problem is solved by means of a custom-designed two-step approach, in order to speed up the solving procedure. Numerical experiments are conducted using data from the Dutch railway network to comparatively evaluate the effectiveness and efficiency of the three proposed approaches with heterogeneous traffic. According to the experimental results, the MILP approach (PTSPO) yields the best overall performance within the required computation time. The experimental results demonstrate the benefits of the integration, i.e., train delays can be reduced by managing train speed.

We study the integration of real-time traffic management and train control by using mixed-integer nonlinear programming (MINLP) and mixed-integer linear programming (MILP) approaches. In Part 1 of the paper (Luan et al., 2018), three integrated optimization problems, namely the PNLP problem (NLP: nonlinear programming), the PPWA problem (PWA: piecewise affine), and the PTSPO problem (TSPO: train speed profile option), have been developed for real-time traffic management that inherently include train control. A two-level approach and a custom-designed two-step approach have been proposed to solve these optimization problems. In Part 2 of the paper, aiming at energy-efficient train operation, we extend the three proposed optimization problems by introducing energy-related formulations. We first evaluate the energy consumption of a train motion. A set of nonlinear constraints is first proposed to calculate the energy consumption, which is further reformulated as a set of linear constraints for the PTSPO problem and approximated by using a piecewise constant function for the PNLP and PPWA problems. Moreover, we consider the option of regenerative braking and present linear formulations to calculate the utilization of the regenerative energy obtained through braking trains. We focus on two objectives, i.e., delay recovery and energy efficiency, through using a weighted-sum formulation and an e-constraint formulation. With these energy-related extensions, the nature of the three optimization problems remains same to Part 1. In numerical experiments conducted based on the Dutch test case, we consider the PNLP approach and the PTSPO approach only and compare their performance with the inclusion of the energy-related aspects; the PPWA approach is neglected due to its bad performance, as evaluated in Part 1. According to the experimental results, the PTSPO approach still yields a better performance within the required computation time. The trade-off between train delay and energy consumption is investigated. The results show the possibility of reducing train delay and saving energy at the same time through managing train speed, by up to 4.0% and 5.6% respectively. In our case study, applying regenerative braking leads to a 22.9% reduction of the total energy consumption.

Application of an M-out-of-N redundancy architecture is a well-known measure for improving the reliability of safety systems. Most scientific papers addressing the reliability assessment of such systems consider a conventional homogeneous M-out-of-N redundancy architecture that is performed for identical channels. However, often in practice, an M-out-of-N redundancy architecture does not have identical channels. Reliability assessment of such heterogeneous systems (electrical/electronic and mechanical) with nonidentical channels and a combination of constant and nonconstant failure rates is considered in this paper. Such type of M-out-of-N redundancy architecture is introduced in this research as "asymmetrical redundancy". It can be used for enhancing the reliability of old mechanical systems or for reducing mutual influence of channels and increase of diagnostic coverage. This paper also presents a new "window-based Markov method" for PFDavg (average probability of failure on demand) and PFH (average frequency of dangerous failures) calculation for systems with an asymmetrical redundancy architecture and compares the results with those obtained by using the steady-state semi-Markov method and Monte-Carlo simulation. The applicability of the developed method is demonstrated in a simple case study.

Belt conveyor systems are widely used in bulk material handling and transport applications. Within a belt conveyor, depending on its distance, there can be tens of thousands of idler rolls which face random failure. However, condition monitoring solutions for belt conveyor idlers is underdeveloped. This is because the choice of monitoring parameters is still arbitrary. This paper aims to investigate which parameters can represent technical condition of idler rolls for the purpose of condition monitoring. A belt conveyor test rig is developed in laboratory. Temperature and vibration sensors are applied to monitor idler rolls induced with different types of failures. Patten of temperature evolution and RMS level of vibration are extracted from the signal and analysed. It is concluded that temperature measurement at roll shafts is a straightforward and effective manner for condition monitoring of belt conveyor idlers.

Purpose: Bulk material-handling equipment development can be accelerated and is less expensive when testing of virtual prototypes can be adopted. However, often the complexity of the interaction between particulate material and handling equipment cannot be handled by a single computational solver. This paper aims to establish a framework for the development, verification and application of a co-simulation of discrete element method (DEM) and multibody dynamics (MBD). Design/methodology/approach: The two methods have been coupled in two directions, which consists of coupling the load data on the geometry from DEM to MBD and the position data from MBD to DEM. The coupling has been validated thoroughly in several scenarios, and the stability and robustness have been investigated. Findings: All tests clearly demonstrated that the co-simulation is successful in predicting particle¿equipment interaction. Examples are provided describing the effects of a coupling that is too tight, as well as a coupling that is too loose. A guideline has been developed for achieving stable and efficient co-simulations. Originality/value: This framework shows how to achieve realistic co-simulations of particulate material and equipment interaction of a dynamic nature.

Shuttle based storage and retrieval systems (SBS/RS) attract continuous research attention because of their ability to achieve a high throughput. In an SBS/RS system, lifts are regarded as the bottleneck that hinder reaching higher throughput and therefore require subtle control polices. In this paper, the scheduling of two non-passing lifts on a common rail SBS/RS has been studied with consideration of the acceleration and deceleration of the lifts. Lift scheduling includes storage and retrieval requests sequencing, assignment of lifts, and collision avoidance. The main objective of the lift scheduling is minimizing the makespan of the moves. Different with the traditional constant velocity lift scheduling approach is that new collisions emerge when the acceleration/deceleration of the lifts are taken into consideration. This makes the scheduling different. In this paper a collision free lifts trajectory predicting approach with acceleration/deceleration is presented. Combined with the collision-free method, request sequencing and assignment are carried out by a proposed genetic algorithm. Experimental results with several SBS/RS practical working scenarios provide evidence that the proposed scheduling approach achieved on average 12.2% and 6.4% improvement in makespan compared with the constant velocity approach when the maximum velocity of the lifts is 1.5 m/s and 2 m/s respectively.

Fresh cut flower supply chains are aware of the need for reducing spoilage and increasing customer satisfaction. This paper focuses on a part of the cut rose supply chain, from auction house to several end customers. A new business mode is considered that would allow end customers to subscribe to florists and have a continuous supply of bouquets of roses. To make this business mode feasible, we propose to benefit from real-time information on roses¿ remaining vase life. First, a quality-aware modeling technique is applied to describe supply chain events and quality change of cut roses among several supply chain players. Then, a distributed model predictive control strategy is used to make up-to-date decisions for supply chain players according to the latest logistics and quality information. This approach provides a tool for multiple stakeholders to collaboratively plan the logistics activities in a typical cut rose supply chain based on roses¿ estimated vase life in real time. The proposed approach is compared with a currently used business mode in simulation experiments. Results illustrate that the new business mode and the planning approach could reduce unmet demand and spoilage in a cut rose supply chain.

In railway operations, when a disruption occurs, train dispatchers aim to adjust the affected schedule and to minimize negative consequences during and after the disruption. As one of the most important components of the railway system, railway signals are used to guarantee the safety of train services. We study the train dispatching problem with consideration of railway signaling commands under the fixed-block signaling system. In such a system, signaling commands dynamically depend on the movement of the preceding trains in the network. We clarify the impact of the signaling commands on train schedules, which has so far been neglected in the literature on railway train dispatching, and we propose an innovative set of signaling constraints to describe the impact. The determination of the signal indicators is presented using ¿if-then¿ constraints, which are further transformed into linear inequalities by applying two transformation properties. Activation of the train speed limits that result from the signaling commands is the core purpose of the signaling constraints, and this is implemented by using the signal indicators. Moreover, we formulate the Greenwave (GW) policy, which requires that trains always proceed under green signals, and we further investigate the impact of the GW policy on delays. In numerical experiments, the proposed signaling constraints are employed within a time-instant optimization problem, which is a mixed-integer linear programming (MILP) problem. The experimental results demonstrate the effectiveness of the proposed signaling constraints and show the impact of the signaling commands and GW policy on the train dispatching solution.

On the basis of an experimental investigation [1], numerical investigation is conducted in this paper on damaged seamless metallic pipelines with metal loss (diameter-to-thickness ratio D/t around 21) through nonlinear finite element method (FEM). Numerical models are developed and validated through test results by using the measured material properties and specimen geometry, capable of predicting the residual ultimate strength of pipes in terms of bending capacity (Mcr) and critical curvature (¿cr). By changing the metal loss parameters, i.e. length (lm), width (wm) and depth (dm), a series of numerical simulations are carried out. Results show that the larger the dm or lm is, the less the bending capacity will be. The increase of notch width slightly reduces the pipe strength, presenting a linear tendency. Based on the FEM results, empirical formulas are proposed to predict the residual ultimate strength of metallic pipes with metal loss under pure bending moment. The prediction results match well with the results from the tests, the numerical simulations as well as the theoretical derivation. Such formulas can be therefore used for practice purposes and facilitate the decision-making of pipe maintenance after mechanical interference.

The combination damage induced by mechanical interference, in reality, is more likely to happen. In this paper, numerical models on pipes with combined dent and metal loss in terms of a notch are developed and validated through tests (diameter-to-thickness ratio D/t of test pipes around 21), capable of predicting the residual ultimate strength of pipes in terms of bending moment (Mcr) and critical curvature (¿cr). The effect of residual stress is explored, assuming a linear distribution in the pipe hoop direction. Investigations of damaged pipes with different D/t (15¿50) are carried out. Through changing damage parameters in the combinations, i.e. dent depth (dd) or metal loss depth (dm), the corresponding effects of damage are clarified. Results show that the combined dent and notch damage is a more severe type of damage on pipe strength compared with other damage types (excluding fracture). The dent in combined damage plays a more dominant role on the pipe residual strength. Empirical formulas are proposed to predict residual ultimate strength of damaged metallic pipes (D/t around 21) with combined dent and metal loss under bending moment, which can be used for practical purposes. The application domain can be expanded to pipes with D/t up to 30 based on simulations.

Wood pellet imports are expected to increase in the European Union and Southeast Asia by 2030, considering pellets are the main feedstock used for co-firing in power plants throughout these regions. Due to the material's physical and biological properties, the equipment at an import terminal need to be different than what is used for other bulk material. Thus, most of the common problems associated with handling can be avoided. Dust emission and explosions, degradation in storage, self-heating and ignition are important criteria when designing a wood pellet port terminal, and can greatly affect associated logistics. Despite some availability of data concerning the handling of pellets, there is a lack of insight into the equipment and operations of actual handling facilities. A detailed literature research was performed in order to ascertain the level of the scientific background on the subject. Subsequently, visits in pellet facilities in the Netherlands and in-depth interviews with representatives were conducted and serve as a means of gaining an overview of current industry practices and equipment used for the handling of wood pellets. The main objective of this work is to evaluate the state-of-the-art in wood pellet handling in import terminals. This way, future bottlenecks can be identified and actions needed to overcome them can be determined. The analysis performed shows that while wood pellet terminals might be able to cope with the low amounts being traded currently, a reexamination and redesign of terminal facilities to accommodate the increased volumes will probably be required by 2030.

Transport demand for containers has been increasing for decades, which places pressure on road transport. As a result, rail transport is stimulated to provide better intermodal freight transport services. This paper investigates mathematical models for the planning of container movements in a port area, integrating the inter-terminal transport of containers (ITT, within the port area) with the rail freight formation and transport process (towards the hinterland). An integer linear programming model is used to formulate the container transport across operations at container terminals, the network interconnecting them, railway yards and the railway networks towards the hinterland. A tabu search algorithm is proposed to solve the problem. The practical applicability of the algorithm is tested in a realistic infrastructure case and different demand scenarios. Our results show the degree by which internal (ITT) and external (hinterland) transport processes interact, and the potential for improvement of overall operations when the integrated optimization proposed is used. Instead, if the planning of containers in the ITT system is optimized as a stand-alone problem, the railway terminals may suffer from longer delay times or additional train cancellations. When planning the transport of 4060 TEU containers within one day, the benefits of the ITT planning without considering railway operations account for 17% ITT cost reduction but 93% railway operational cost growth, while the benefits of integrating ITT and railway account for a reduction of 20% in ITT cost and 44% in railway operational costs.

Eddy current pulsed thermography (ECPT) is well established for non-destructive testing of electrical conductive materials, featuring the advantages of contactless, intuitive detecting and efficient heating. The concept of divergence characterization of the damage rate of carbon fibre-reinforced plastic (CFRP)-steel structures can be extended to ECPT thermal pattern characterization. It was found in this study that the use of ECPT technology on CFRP-steel structures generated a sizeable amount of valuable information for comprehensive material diagnostics. The relationship between divergence and transient thermal patterns can be identified and analysed by deploying mathematical models to analyse the information about fibre texture-like orientations, gaps and undulations in these multi-layered materials. The developed algorithm enabled the removal of information about fibre texture and the extraction of damage features. The model of the CFRP-glue-steel structures with damage was established using COMSOL Multiphysics® software, and quantitative non-destructive damage evaluation from the ECPT image areas was derived. The results of this proposed method illustrate that damaged areas are highly affected by available information about fibre texture. This proposed work can be applied for detection of impact induced damage and quantitative evaluation of CFRP structures.

Deep sea mining was identified in the middle of last century. However, its industrialization and commercialization today are limited in the costal mining industry due to the high mining cost and technical issues. The purpose of this paper is to analyze a green transport plan of deep sea mining systems in terms of the optimal efficiency of the rigid pipe lifting system and the total energy consumption. The deep sea mining facilities considered in this paper consist of a mineral collecting machine, a flexible hose, a rigid pipe, a grinding machine, a concentrating machine and a horizontal pipe conveyor. Centrifugal pump modelling and its working principle are researched, because it is the major transport facility. The relationship between the optimal efficiency, total energy consumption, transport loss factor, and the relating mining parameters is determined by numerical simulations and fittings under Fortran and Matlab environment, and the optimization under 1st Opt environment. The research conducted in this paper is valuable for the pre-evaluation of deep sea mining transport systems and the further realization of its industrialization and commercialization process.

This paper investigates the optimization of biomass terminal equipment deployment. A mixed integer linear programming model is developed and applied to minimize the terminal's investment and operational costs related to dedicated and partially used or shared equipment between a terminal's operational steps. The results minimize annual terminal costs through equipment and infrastructure selection and utilization. Tipping points where the technology and equipment type or size change in relation to the increasing throughput are highlighted. Analytical results emphasize the importance of storage costs in all biomass terminals, as well as the critical influence of operational costs in larger facilities.

A dent is one of the main structural damages that may affect ultimate strength. In this paper, the residual ultimate strength of dented metallic pipes subjected to a bending moment is quantitatively investigated. The numerical model is developed accounting for the variation of the dent length (ld), dent depth (dd), dent width (wd), dent rotation angle (¿d) and dent location based on ABAQUS Python. The numerical model is validated by test results from a four-point bending test. Subsequently, a parametric investigation is performed on the effects of wave-type initial imperfection, D/t and dent geometrical parameters. It is found that both ld and dd have a significant effect on the residual ultimate strength of dented metallic pipes, while the effect of wd is slight. Finally, an empirical formula with respect to ld and dd has been proposed for the prediction of bending moment, which can be deployed for practical purposes.

Waterborne autonomous guided vessels (waterborne AGVs) moving over open waters experience environmental uncertainties. This paper proposes a novel cost-effective robust distributed control approach for waterborne AGVs. The overall system is uncertain and has independent subsystem dynamics but coupling objectives and state constraints. Waterborne AGVs determine their actions in a parallel way, while still minimizing an overall cost function and respecting coupling constraints robustly by communicating within a neighborhood. Our first contribution is the proposal of the system robustness level for the cost-effective robust distributed model predictive control (RDMPC) for waterborne AGVs. Cost-effective RDMPC models the price of robustness by explicitly considering uncertainty and system characteristics in a tube-based robust control framework. The second contribution is an efficient integrated branch bound (BB) and the alternating direction method of multipliers (ADMMs) algorithm for solving the cost-effective RDMPC problem. The algorithm exploits special ordered variable sets and combining branching criteria with intermediate ADMM results conducting smart search in BB. Simulation results demonstrate the effectiveness of the proposed approach for cooperative distributed waterborne AGVs with cost-effective robustness.

Purpose: Sliding wear is a common phenomenon in the iron ore handling industry. Large-scale handling of iron ore bulk-solids causes a high amount of volume loss from the surfaces of bulk-solids-handling equipment. Predicting the sliding wear volume from equipment surfaces is beneficial for efficient maintenance of worn equipment. Recently, the discrete element method (DEM) simulations have been utilised to predict the wear by bulk-solids. However, the sensitivity of wear prediction subjected to DEM parameters has not been systemically investigated at single particle level. To ensure the wear predictions by DEM are accurate and stable, this study aims to conduct the sensitivity analysis at the single particle level. Design/methodology/approach: In this research, pin-on-disc wear tests are modelled to predict the sliding wear by individual iron ore particles. The Hertz-Mindlin (no slip) contact model is implemented to simulate interactions between particle (pin) and geometry (disc). To quantify the wear from geometry surface, a sliding wear equation derived from Archard's wear model is adopted in the DEM simulations. The accuracy of the pin-on-disc wear test simulation is assessed by comparing the predicted wear volume with that of the theoretical calculation. The stability is evaluated by repetitive tests of a reference case. At the steady-state wear, the sensitivity analysis is done by predicting sliding wear volumes using the parameter values determined by iron ore-handling conditions. This research is carried out using the software EDEM® 2.7.1. Findings: Numerical errors occur when a particle passes a joint side of geometry meshes. However, this influence is negligible compared to total wear volume of a wear revolution. A reference case study demonstrates that accurate and stable results of sliding wear volume can be achieved. For the sliding wear at steady state, increasing particle density or radius causes more wear, whereas, by contrast, particle Poisson's ratio, particle shear modulus, geometry mesh size, rotating speed, coefficient of restitution and time step have no impact on wear volume. As expected, increasing indentation force results in a proportional increase. For maintaining wear characteristic and reducing simulation time, the geometry mesh size is recommended. To further reduce simulation time, it is inappropriate using lower particle shear modulus. However, the maximum time step can be increased to 187% TR without compromising simulation accuracy. Research limitations/implications: The applied coefficient of sliding wear is determined based on theoretical and experimental studies of a spherical head of iron ore particle. To predict realistic volume loss in the iron ore-handling industry, this coefficient should be experimentally determined by taking into account the non-spherical shapes of iron ore particles. Practical implications: The effects of DEM parameters on sliding wear are revealed, enabling the selections of adequate values to predict sliding wear in the iron ore-handling industry. Originality/value: The accuracy and stability to predict sliding wear by using EDEM® 2.7.1 are verified. Besides, this research accelerates the calibration of sliding wear prediction by DEM.

Large-scale handling of particulate solids can cause severe wear on bulk solids handling equipment surfaces. Wear reduces equipment life span and increases maintenance cost. Examples of traditional methods to reduce wear of bulk solids handling equipment include optimizing transport operations and utilizing resistant materials. To our knowledge, the so-called bionic design has not been utilized. Bionic design is the application of biological models, systems, or elements to modern engineering. Bionic design has promoted significant progress on the development of engineering products and systems. In order to use bionic design for wear reduction of bulk solids handling equipment surfaces, this paper introduces bionic design to bulk solids handling on the basis of analogies between biology and bulk solids handling. In addition, a bionic design methodology for the wear reduction of bulk solids handling equipment surfaces is formulated. Based on the bionic design methodology, two bionic models used for abrasive and erosive wear reduction of bulk solids handling equipment surfaces are proposed.

Belt conveyors can be partially loaded due to the variation of bulk material flow loaded onto the conveyor. Speed control attempts to reduce the belt conveyor energy consumption and to enable the green operations of belt conveyors. Current research of speed control rarely takes the conveyor dynamics into account so that speed control lacks applicability. Based on our previous research, this paper will provide an improved three-step method to determine the minimum speed adjustment time. This method can be summarized as Estimation-Calculation-Optimization and ECO in short. The ECO method takes both the potential risks and the conveyor dynamics into account. It is expected to keep belt conveyors in good dynamic behaviors in transient operations. After discussing the ECO method, this research takes a long inclined belt conveyor of an import dry bulk terminal as case study. Based on the suggested acceleration time, a speed controller is built and computational simulations are carried out to evaluate the energy savings and the conveyor dynamics. Experimental results prove that the application of the ECO method ensures the healthy dynamic performance of belt conveyors under speed control in transient operations. Annually, the average electricity consumption of the single conveyor can be reduced by over 10% with around 90 tons reduction of CO2 emission. The direct economic benefit can reach up to more than ¿10,000 in terms of the electricity utilization per year.

The handling of iron ore bulk solids maintains an increasing trend due to economic development. Because iron ore particles have hard composites and irregular shapes, the bulk solids handling equipment surface can suffer from severe sliding wear. Prediction of equipment surface wear volume is beneficial to the efficient maintenance of worn areas. Archard¿s equation provides a theoretical solution to predict wear volume. To use Archard¿s equation, the coefficient of sliding wear must be determined. To our best knowledge, the coefficient of sliding wear for iron ore handling conditions has not yet been determined. In this research, using a pin-on-disk tribometer, the coefficients of sliding wear for both Sishen particles and mild steel are determined with regard to iron ore handling conditions. Both naturally irregular and spherical shapes of particles are used to estimate average values of wear rate. Moreover, the hardness and inner structures of Sishen particles are examined, which adds the evidence of the interpretation of wear results. It is concluded that the coefficients of sliding wear can vary largely for both Sishen particle and mild steel. The wear rate decreases from transient- to steady-state. The average coefficient of sliding wear is capable of predicting wear with respect to long distances at the steady-state. Two types of sliding friction are distinguished. In addition, it is found that the temperature rise of the friction pairs has negligible influence on wear rate.

In modern logistics chain, planning system which been applied for supporting daily operations, is becoming more information-intensive and technologically-dependent. Due to the growing operational complexities, the planning system is not only required to focus on ensuring the feasibility of daily plan, but also be capable of manipulating conflict of interest (COI) by exploiting efficient negotiation. This paper addresses a challenge of hinterland transport planning caused by limited information sharing, lack of collaboration and COI. We design collaboration and decision-making mechanisms for the implementation of autonomous control by means of multi agent technology and hybrid heuristics. It aims at providing quality plan to achieve high level of performance and robustness in hinterland logistics. From a system point of view, a service oriented architecture is proposed to integrate agent paradigm with a web-based planning system. From an operational point of view, special attentions are paid on establishing multi-dimensional collaborations between different stakeholders under the support of game theoretic approach. Specifically, we define how planning activities are executed, which level of collaborations are incorporated and how benefits are achieved with a global point of view. Due to the NP-hard nature of the addressed problem, an integrated NGSA-II and simulated annealing algorithm is implemented for assisting decision making. The parameters associated with the algorithm are tuned based on the Taguchi method. Case and comparative study will be presented to validate the appropriateness and performance of the approach.

Inland vessels are often used to transport containers between large seaports and the hinterland. Each time a vessel arrives in such a port, it typically visits several terminals to load and unload containers. In the Port of Rotterdam, the largest port in Europe, there are 77,000 inland vessels that have moored in the port in 2014 for transporting cargo. With the significant growth of containerized cargo transportation over the last decade, large seaports are under pressure to ensure high handling efficiency. Due to this development and the limited capacity at terminals, the inland vessels usually spend longer time in the port that originally planned. This leads to low utilization of terminal resources and congestion in the port. This paper proposes a novel two-phase planning approach that could improve this, taking into account several practical constraints. Specifically, we take into account the restricted opening times of terminals, the priority of sea-going vessels, and the different terminal capacities and sizes. In addition, we also consider the option for inland vessels to carry out additional inter-terminal transport tasks. Our approach is based on the integration of mixed-integer programming (MIP) and constraint programming (CP) to generate rotation plans for inland vessels. In the first phase, a single vessel optimization problem is solved using MIP. In the second phase, a multiple vessel coordination problem is formulated using CP; three large neighborhood search (LNS)-based heuristics are proposed to solve the problem. Simulation experiments show that the proposed LNS-based heuristic outperforms the performance obtained with a state-of-the-art commercial CP solvers both regarding the solution quality and the computation time. Moreover, the simulation results indicate significant improvements with shorter departure times, sojourn times and waiting times.

In the literature, the continuous line bucket (CLB) lifting system and the pipe lifting system (PLS), as two typical mineral lifting methods in deep sea mining (DSM) systems, have been discussed since the 1960s. The purpose of this paper is to determine an appropriate lifting method for deep sea mining systems at different working conditions. The determination is based on the comparison of the analysis results of the two typical lifting methods considering the technology performance and the profitability. The analysis is based on a numerical calculation performed in a MATLAB environment. This paper shows the comparison of the results of the CLB system and PLS in terms of the lifting efficiency, the energy consumption, and the profitability. The research reported in this paper can be utilized to select a proper lifting method for a DSM project depending on its specific criteria analysis.

Condition monitoring systems are commonly exploited to assess the health status of equipment. A fundamental part of any condition monitoring system is data acquisition. Meaningfully estimating the current condition and predicting the future behaviour of the equipment strongly depend on the characteristic of the data measurement stage. Nowadays, condition monitoring has wide applications in the railway industry, and various monitoring approaches have been proposed for the inspection of wheel and rail conditions. In-service condition monitoring of wheels provides the real-time data required for maintenance planning, while in-workshop inspection is normally done at fixed intervals carried out periodically. In-service data acquisition can be divided into on-board and wayside measurements. In this paper, on the basis of these classifications, the existing data acquisition techniques for the monitoring of railway wheel condition are reviewed, and the state-of-the-art methods and required research are discussed.

We address the problem of simultaneously scheduling trains and planning preventive maintenance time slots (PMTSs) on a general railway network. Based on network cumulative flow variables, a novel integrated mixed-integer linear programming (MILP) model is proposed to simultaneously optimize train routes, orders and passing times at each station, as well as work-time of preventive maintenance tasks (PMTSs). In order to provide an easy decomposition mechanism, the limited capacity of complex tracks is modelled as side constraints and a PMTS is modelled as a virtual train. A Lagrangian relaxation solution framework is proposed, in which the difficult track capacity constraints are relaxed, to decompose the original complex integrated train scheduling and PMTSs planning problem into a sequence of single train-based sub-problems. For each sub-problem, a standard label correcting algorithm is employed for finding the time-dependent least cost path on a time-space network. The resulting dual solutions can be transformed to feasible solutions through priority rules. Numerical experiments are conducted on a small artificial network and a real-world network adapted from a Chinese railway network, to evaluate the effectiveness and computational efficiency of the integrated optimization model and the proposed Lagrangian relaxation solution framework. The benefits of simultaneously scheduling trains and planning PMTSs are demonstrated, compared with a commonly-used sequential scheduling method.

This brief proposes a distributed predictive path following controller with arrival time awareness for multiple waterborne automated guided vessels (waterborne AGVs) applied to interterminal transport (ITT). The goal is to design an efficient cooperative distributed algorithm that solves local problems in parallel and minimizes an overall objective. We model the ITT problem using waterborne AGVs with independent dynamics and objectives but coupling collision avoidance constraints. The problem is then solved by distributed model predictive control (DMPC) of which the parallelism is realized using the alternating direction method of multipliers (ADMM). Successive linearizations are utilized to maintain a tradeoff among computational complexity, optimality, and ease of decomposition. Moreover, we propose a fast ADMM by iteratively incorporating in local problems adaptive global information to improve convergence rates. Simulation results for an ITT case study illustrate the effectiveness of the proposed algorithms for DMPC of time-varying networks in general and cooperative distributed waterborne AGVs in particular.

As the common metal structure type, welded structures are widely used in civil infrastructure, bridges, ships and engineering machinery. Fatigue cracks often originate in welds enduring intense stress concentration or in welding defects under long-Term continuous alternating loading [1]. Once these cracks propagate to a critical length, the structural integrity will be challenged. As a result, welding cracks detection is significant in engineering applications.

Biomass is the largest source of renewable energy carrier in the European Union (EU) contributing to over 60% of renewable energy, with the majority of supply coming from domestic sources. However, an increasing significant amount of feedstock is imported, either due to domestic undersupply or higher production costs within the country. This article provides an up-to-date view of bioenergy supply, demand and trade in Northwest Europe to 2030. Projections of the energy system model Green-X are compared to recent national studies concerning bioenergy imports. The results show that there is a sizeable gap of the projection bandwidths after the 2020 horizon. Projections might under- or overestimate biomass potential in certain cases, depending on whether they are derived from national reports or regional models, whether future policy developments were taken into account etc. The ranges of biomass consumption are multiple times apart by 2020 already, and the gap increases by 2030. Total biomass imports in the region can range between 14 and 44.3 Mt by 2020 and 18.5¿60 Mt by 2030.

This paper addresses two coordination problems that exist in the waterborne transport in large seaports, the long time of stay of inland vessels and insufficient terminal and quay crane planning with respect to their sailing schedules. A novel coordination model is proposed and tackled using logic-based Benders decomposition and Large Neighborhood Search. In addition, a closed-loop perspective is taken, in which possible disturbances that may occur are considered. Simulation results show that our approach can scale to real-world sizes and provide better schedules for inland vessels within the port. The potential of using inland vessels for inter-terminal transport is also extensively investigated.

We propose closed-loop energy-efficient scheduling and control of an autonomous Inter Terminal Transport (ITT) system using waterborne Autonomous Guided Vessels (waterborne AGVs). A novel pick-up and delivery problem considering safety time intervals between berthing time slots of different waterborne AGVs is proposed. Waterborne AGVs are controlled in a cooperative distributed way to carry out the assigned schedules. Real-time scheduling and control loop is closed by a partial scheduling model and an interaction model with feedback reflecting neglected lower level factors. Simulation results demonstrate the effectiveness of the proposed methodology and the potential of applying waterborne AGVs towards an autonomous ITT system.

This paper presents a review of the troughability test specified in standard ISO 703 and associated models for quantifying the effective modulus of elasticity for uniform belt bending stiffness. For the interpretation of the test results, four analytical methods are employed: two theoretical ones that assume inextensible nonlinear bending of the belt's structure using the Euler¿Bernoulli beam theory, and a Finite Element Method (FEM). The latter includes not only bending, but also stretching and shear effects, accommodating the Timoshenko theory for model with beam elements and the Mindlin¿Reissner theory for model with shell elements. The present study compares the models, gives recommendations regarding their application and usage limitations. The impact of the varying effective modulus of elasticity, line mass and geometry on the belt's troughability is investigated within established parameters and limitations inherent to conveyor belts. The results indicate that the troughability test (ISO 703) in combination with an appropriate choice of the model for data extraction can be used for quantifying the effective modulus of elasticity. This conclusion is limited to small strain conditions (up till 5%). Analyses reveal that thick and narrow belts with a small belt width-to-thickness ratio reach this strain limitation at smaller troughability values.

Numerical techniques have increasingly been used to model fluid¿particle two-phase flows. Coupling the immersed boundary method (IBM) and discrete element method (DEM) is one promising approach for modeling particulate flows. In this study, IBM was coupled with DEM to improve the reliability and accuracy of IBM for determining the positions of particles during the sedimentation process within viscous fluids. The required ratio of the particle diameter to the grid size (D/dx) was determined by comparing the simulation results with the analytical solution and experimental data. A dynamic mesh refinement model was utilised in the IBM model to refine the computational fluid dynamics grid near the particles. In addition, an optimum coupling interval between the IBM and DEM models was determined based on the experimental results of a single particle sedimentation within silicon oil at a Reynolds number of 1.5. The experimental results and the analytical solution were then utilised to validate the IBM¿DEM model at Reynolds numbers of 4.1, 11.6, and 31.9. Finally, the validated model was utilised to investigate the sedimentation process for more than one particle by modeling the drafting-kissing-tumbling process and the Boycott phenomenon. Benchmark tests showed that the IBM¿DEM technique preserves the advantages of DEM for tracking a group of particles, while the IBM provides a reliable and accurate approach for modeling the particle¿fluid interaction.

The latest research progress on residual ultimate strength of metallic pipelines with structural damage is presented through literature survey. The investigated pipe diameter-to-thickness ratios majorly lie between 20 and 50, which are typically applicable in deep water. Influential parameters in terms of pipe load, installation process and material that affect the ultimate strength of pipes are categorised. Structural damage including dent, metal loss and crack is identified and efforts are made to summarise critical damage factors such as dent length and crack depth. Furthermore, research and prediction methods on pipe residual ultimate strength in terms of experimental tests, numerical simulations and analytical predictions are summarised and discussed. Specific details on how to introduce, simplify and simulate structural damage are presented and discussed. It is expected that the mechanism of residual ultimate strength of metallic pipes with structural damage can be clarified through this study so that guidance will be provided for researchers in this field.

Most analytical formulas developed for the PFD and PFH calculation assume a constant failure rate. This assumption does not necessarily hold for system components that are affected by wear. This article presents methods of analytical calculations of PFD and PFH for an M-out-of-N redundancy architecture with nonconstant failure rates and demonstrates its application in a simple case study. The method for PFD calculation is based on the ratio between cumulative distribution functions and includes forecasting of PFD values with a possibility of update of failure rate function. The approach for the PFH calculation is based on simplified formulas and the definition of PFH. In both methods, a Weibull distribution is used for characteristics of the system behavior. The PFD and PFH values are obtained for low, moderate and high degradation effects and compared with the results of exact calculations. Presented analytical formulas are a useful contribution to the reliability assessment of M-out-of-N systems.

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

The current weaknesses of the conventional intermodal freight transportation system have led to the development of the synchromodal freight transportation concept introduced and piloted in the Netherlands. The innovative concept has the advantage of adding flexibility, cost reduction, and sustainability among other things, into the freight transportation system. The synchromodal system has not been started in any developing country yet due to its newness. In this study, we used multiple methodologies to conduct a feasibility study for the possibilities of introducing the concept in a developing country, Ghana. An intensive literature review was performed using the Grounded Theory and the Critical Success Factors (CSFs) method to identify the key factors for the introduction of the synchromodal concept. Questionnaires were administered to the primary stakeholders in the maritime-hinterland transportation sector to solicit their views about the factors necessary for the implementation. We next carried out SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to catalogue the strengths and weakness of the country in introducing the concept. The multiple regression analysis method was used to analyse the experience of stakeholders in the freight transportation business and their knowledge about the synchromodal freight transportation system. The results of the study show that it is possible to introduce the concept in the country. However, there is the need to improve the current transportation and ports infrastructure of the country considerably for successful synchromodal system adaptation. There is also the need for stakeholders education on the concept.

Deep sea mining tailings disposal is a new environmental challenge related to water pollution, mineral crust waste handling, and ocean biology. The objective of this paper is to propose a new tailings disposal procedure for the deep sea mining industry. Through comparisons of the tailings disposal methods which exist in on-land mining and the coastal mining fields, a new tailings disposal procedure, i.e., the submarine¿backfill¿dam¿reuse (SBDR) tailings disposal procedure, is proposed. It combines deep sea submarine tailings disposal, backfill disposal, tailings dam disposal, and tailings reuse disposal for the deep sea mining industry. Then, the analytic network process (ANP) method is utilized to evaluate the performances of different tailings disposal methods. The evaluation results of the ANP show that the new proposed tailings disposal procedure is the most suitable for the deep sea mining industry.

Belt conveyors play an important role in continuous dry bulk material transport. Large scale belt conveyor systems consume a considerable amount of electricity. The approach of controlling the belt speed in such a way that the belt's volumetric capacity is fully utilized under all operational conditions has been proven to significantly reduce the energy consumption of a belt conveyor. Current research on speed control for belt conveyors mainly focuses on the calculation and the prediction of possible energy savings. Few studies focus on the dynamics of belt conveyors in transient operation. There are however no studies that describe the operation of speed controlled belt conveyors during transient operation. This paper presents a three-step method that can be used to determine a proper way to accelerate a speed controlled belt conveyor during transient operation. This method takes the potential risks in transient operation and the conveyor dynamic performance into account. A case of horizontal conveyor system is studied and the three-step method is applied. In the case study, a predictor of the permitted maximum acceleration is calculated. Simulations with the predicted acceleration time are carried out to determine the acceleration operation and to analyse the conveyor dynamics. The simulations are based on an existing finite element model of a belt conveyor.

The objective of this study is to determine the pressure distribution caused by bulk material on a loaded conveyor belt using theoretical and experimental approaches. The determination of the pressure distribution is important for the engineering design of conveyor belts and the analysis of the belt-bulk material interaction. A theoretical model has been developed to predict the pressure distribution but not fully verified yet. There has been no satisfactory method for the direct measurement of the pressure. Using a tactile pressure sensor, we measured the pressure distribution directly on a running conveyor belt. The measured pressure is assessed using a conveyor scale. High pressure regions are identified. Comparisons between theoretical and experimental results indicate that a good correlation has been achieved and the theoretical model is further verified. The study attests the applicability of both theoretical and experimental approaches for the determination of the pressure distribution on loaded conveyor belts.

Purpose - The macroscopic properties of dried sand can be correctly modelled when the accurate determination of the microscopic properties is available. The microscopic properties between the particles such as the coefficients of rolling (µr) and sliding (µs), are numerically determined in two different ways: with and without considering the fluid effect. In an earlier study, the microscopic properties were determined by discrete element method (DEM) and without considering the air effect on the macroscopic properties such as the Angle of Repose. The purpose of this paper is to recalibrate the microscopic properties through a coupling between the DEM and computational fluid dynamics (CFD). Design/methodology/approach - The first step is dedicated to the calibration of the CFD-DEM model through modelling a single particle sedimentation within air, water, and silicon oil. The voidage and drag models, the grid size ratio (D/dx), the domain size ratio (W/D), and the optimum coupling interval between the CFD and DEM were investigated through comparing the CFD-DEM results with the analytical solution and experimental data. The next step is about modelling an Hourglass with the calibrated CFD-DEM model to recalibrate the µr and µs of dried sand particles. Findings - It was concluded that the air has a minor effect on the macroscopic properties of the dried sand and the µr and µs that were obtained with the DEM can be utilized in the CFD-DEM simulation. Originality/value - Utilizing the granulometry of dried quartz sand in the calibration process of the CFD-DEM method has raised the possibility of using the µr and µs for other applications in future studies.

Purpose - The tensile test is one of the fundamental experiments used to evaluate material properties. Simulating a tensile test can be a replacement of experiments to determine mechanical parameters of a continuous material. The paper aims to discuss these issues. Design/methodology/approach - This research uses a new approach to model a tensile test of a high-carbon steel on the basis of discrete element method (DEM). In this research, the tensile test specimen was created by using a DEM packing theory. The particle-particle bond model was used to establish the internal forces of the tensile test specimen. The particle-particle bond model was first tested by performing two-particle tensile test, then was adopted to simulate tensile tests of the highcarbon steel by using 3, 678 particles. Findings - This research has successfully revealed the relationships between the DEM parameters and mechanical parameters by modelling a tensile test. The parametric study demonstrates that the particle physical radius, particle contact radius and bond disc radius can significantly influence ultimate stress and Young's modulus of the specimen, whereas they slightly impact elongation at fracture. Increasing the normal and shear stiffness, the critical normal and shear stiffness can enable the increase of ultimate stress, however, up to maximum values. Research limitations/implications - To improve the particle-particle bond model to simulate a tensile test for high-carbon steel, the damping factors for compensating energy loss from transition of particle motions and failure of bonds are required. Practical implications - This work reinforces the knowledge of applying DEM to model continuous materials. Originality/value - This research illustrates a new approach to model a tensile test of a high-carbon steel on the basis of DEM.

This work tackles the problem of controlling operations at an automated container terminal. In the context of large supply chains, there is a growing trend for increasing productivity and economic efficiency. New optimization models and algorithms are provided for scheduling and routing equipment that is moving containers in a quay area, loading/unloading ships, transporting them via Automated Guided Vehicles (AGVs) to Automated Stacking Cranes (ASCs), organizing them in stacks. In contrast with the majority of the approaches in the related literature, this work tackles two dynamics of the system, a discrete dynamic, characteristic of the maximization of operations efficiency, by assigning the best AGV and operation time to a set of containers, and a continuous dynamic of the AGV that moves in a geographically limited area. As an assumption, AGVs can follow free range trajectories that minimize the error of the target time and increase the responsiveness of the system. A novel solution framework is proposed in order to tackle the two system dynamics. Various metaheuristic algorithms are tested to solve the problem in a near-optimal way. Computational experiments are presented in order to show the feasibility of the proposed framework on a practical case study, and to assess the performance of advanced scheduling and routing algorithms on numerous system settings.

The singularities of parallel manipulators are usually identified by geometrical methods or by the kinematic principles based on the pose parameters. The methods have limitations in applications that involve singularity avoidance, such as motion planning from input parameters. To identify a singularity from an input parameter point of view, which would make the singularity avoidance strategy more direct and more effective in practical applications, this paper focuses on the relationship between the singularities, the configuration spaces and the input parameters with a 3SPS+1PS parallel hip joint simulator selected to implement this approach. A univariate-form polynomial equation of the forward kinematics is obtained with the aid of the Sylvester dialytic method of elimination, therefore proving that the manipulator has at most eight configurations for a single input. The configurations are then divided into two types of spaces according to their distributions. It is discovered that in practice, we only need concern ourselves with the basic configuration spaces, where the singular loci degenerate into a single surface. Finally, the singular condition is proved to be equivalent to that when the univariate-form input¿output equation has a repeated root in the real number field. Therefore, the singular condition equation of the input parameters and the singular loci of the input parameters in the basic configuration spaces are obtained. This study provides new insight into the singularity avoidance of a parallel manipulator, especially for the singularity-free design in the motion planning from input parameters.

During the past decade, inland vessels have gained importance in container transport because of their reliability, low environmental impact, and major capacity for increased exploitation. Although inland vessels are crucial in container transport between terminals in the port and the hinterland, in a large seaport like the one in Rotterdam, Netherlands, only 62% of the inland vessels leave the port on time. The other vessels have to stay in the port area for a longer time than planned. This situation leads to uncertainty in waiting times of vessels at terminals and low utilization of terminal quay resources. A two-phase approach is proposed that integrates mixed-integer programming (MIP) and constraint programming (CP) to solve the problem by generating optimal rotation plans for inland vessels. In the first phase, the single-vessel optimization problem is formulated on the basis of MIP and solved with state-of-the-art MIP solvers. In the second phase, the multiple-vessel coordination problem is formulated on the basis of CP, and a large neighborhood search-based heuristic is proposed to solve the problem. Commercial CP solvers are also used for comparison. Simulation results show that the proposed large neighborhood search-based heuristic outperforms the commercial CP solver with regard to both the solution quality and the computation time. Moreover, simulation results with respect to departure time of the last vessel, total sojourn time, and waiting time show significant improvement with earlier departure times and shorter sojourn times and waiting times.

A distributed constraint optimization problem (DCOP) is a description of constraint optimization problem where variables and constraints are distributed among a group of agents, and where each agent can only interact with agents that share constraints. Even though DCOPs have been studied since the 1990s, there are only a few attempts to address real world problems using this formalism, mainly because of the complexity of the solution algorithms. In this paper, we compare 4 state-of-the-art DCOP approaches to solve the vessel rotation planning problem (VRPP), which concerns deciding on the optimal sequence of vessel visits to different terminals in a large seaport. We hereby also consider two agent structures: a single layer and a multi-layer structure. For each of the structures, we compare the four different algorithms for solving DCOPs, aiming at studying how the algorithms perform in VRPPs of increasing sizes. We assess the methods based on the size and quantity of messages exchanged, computation time, and quality of solutions.

This paper presents an improved zero vibration method for the swing control of bridge-type grab ship unloader. With the method, the concepts of equivalent frequency and the equivalent damping ratio are proposed to cope with the changeable length of rope, and the optimal path planning is considered to avoid collision and improve efficiency. Numerical simulation results of a case study indicate that the maximum residual swing angle of the grab can be limited to a small range to ensure safety using the improved zero vibration method, whereas the traditional zero vibration method with average frequency and zero damping ratio gets poor results of swing control. After that, the sensitivities of the max residual swing angle to the changes of some main design parameters (damping coefficient, deviation of the center of gravity of the grab in rope direction, and time delay of the system) and operating parameters (position deviation of the trolley, initial length deviation of the rope, and initial swing angle) are analyzed. The results obtained display that the residual swing angle is sensitive to the deviation of grab's center of gravity, the deviation of trolley's position, and the initial swing angle under the same control parameters, but insensitive to the damping coefficient, the time delay of the system, and the initial length deviation of the rope. This can help to select the appropriate parameter values or adaptive range in an actual unloader.

Large ports are seeking innovative logistical ways to improve their competitiveness world-wide. This article proposes waterborne AGVs, inspired by conventional automated guided vehicles and autonomous surface vessels, for transport over water. A predictive path following with arrival time awareness controller is proposed for such waterborne AGVs. The controller is able to achieve smooth tracking and energy efficiency with arrival time awareness for transport oriented applications. Tracking errors are conveniently formulated with vessel dynamics modeled in connected reference path coordinate systems and a coordinate transformation at switching coordinate systems. Binary decision variables and logic constraints based on an along-track state are proposed for modeling switches in the framework of Model Predictive Control (MPC) so that overshoots are avoided. Moreover, timing-aware along-track references are generated by a two-level double integrator scheme. The lower level is embedded in online MPC optimizations for smooth tracking. The higher level solves a mixed-integer quadratic programming problem considering distance-to-go and time-to-go before each MPC optimization. References over the next prediction horizon are generated being aware of the requirements on arrival time. Furthermore, successive linearizations of nonlinear vessel dynamics about a shifted previous optimal system trajectory are implemented to maintain a trade-off between computational complexity and optimality. Simulation results of two industrially relevant Inter Terminal Transport case studies illustrate the effectiveness of the proposed modeling and control design for waterborne AGVs.

Dust generation is related to the durability of products, in other words the wear rate of particles subject to forces. During transport, storage and handling the wood pellets are undergoing different forces within different pieces of equipment. For example impact forces when particles fall down or impact geometries and compressive forces when in storage. The objective of this paper is to assess the representativeness of the socalled tumbling can test in relation to handling conditions in the supply chain for wood pellets. Therefore forces acting on particles in the tumbling can on the one side and during loading and discharging of a flat bottom silo on the other side were compared by Discrete Element Model simulations. It can be concluded that in the presented cases the tumbling can underestimates the handling conditions of the material in reality.

This paper presents a new approach to determine the bending stiffness of a pipe conveyor belt that is sufficient to form a stable pipe shape based on its throughability performance. The paper describes the mathematical model that determines pipe conveyor contact forces and introduces two numerical models solved using FEM in ANSYS. Results agree with the experimental data obtained using a six-point stiffness device. The mathematical model proposed can be used as a uniform validation technique for any numerical model. Appearance of one of the contact forces that equals zero is considered as a criterion for insufficient bending stiffness of belt to form a stable pipe shape. Effective modulus of elasticity quantified from the throughability parameter becomes a link to express belt pipe-ability. Impact of belt line mass and bending stiffness is investigated: for the same belt geometry, heavier belts require higher bending stiffness for the correct pipe shape formation.

A shuttle-based storage and retrieval system (SBS/RS) is a relatively new material-handling facility. A multi-elevator tier-captive SBS/RS is a newly designed subset of such a facility. This new system consists of tier-captive shuttle carriers, multiple elevators with a lifting table, and racks. The storage rack of the system is defined in terms of tiers, columns, and the number and position of the elevators. The aim of this study is to develop an efficient simulation model that can be auto-remodeled for different rack configurations. With this model, it will be easy for warehouse designers to test a large number of rack alternatives and to determine the optimal solution efficiently. Furthermore, the designers can illustrate the solution to shareholders through animation identical to the real system. A simulation case study is presented for a multi- elevator tier-captive SBS/RS containing 81 different rack alternatives. These alternatives are simulated under 15 different retrieval rates within 48¿h, and finally, the optimal rack design is found out. We believe that our work will assist warehouse designers in efficiently designing racks of multi- elevator tier-captive SBS/RSs during early technology selection.

In this paper simulation is applied to design belt conveyor networks at dry bulk terminals. Stochastic variations in ship interarrival times, shiploads and equipment availabilities enforce the use of simulation. Parameters that affect belt conveyor network designs like the network connectivity, storage policy and stochastic distributions are evaluated in this paper. One of the main findings is that installing the maximum number of connections does not necessarily lead to better performances. Another finding is that redundancy of piles (a pile is in reach of two stockyard machines) is more efficient than increasing the number of connections. In a case study, designs for belt conveyor networks were formulated and assessed using the simulation model developed.

Innovations of information and communication technology (ICT) open plenty opportunities to promote internal operation efficiency and external service level in logistics. As current logistics developments tend to be more complex in operation and large in scale, recent practices start to pay more attentions on improving asset (e.g. equipment and infrastructure) management performance with new ICT development. One of the primary concern is to improve system robustness and reliability. It not only requires the supervision system be capable of diagnosing the condition of the system, but also proficient to find the intrinsic relationship between different conditions and resources thus lead to an integrated decision making process. Moreover, recent ICT innovations, such as WSN and IOT, could record and deliver system descriptors (physical measurements, virtual resources, operational configurations) in real time. Such large-stream and heterogeneous data requires an integrated framework to process and management. To address such challenges, in this paper, a novel concept of context-aware supervision is proposed. An intelligent system with integration of semantic web and agent technology is developed, which aims at providing condition-monitoring and maintenance decisions to relevant user. A generic ontology-agent based framework will be illustrated. The developed system will be applied for the supervision of a large-scale material handling system-belt conveying system as a proof-of-concept.

Transportation of perishables such as fruits and vegetables with short shelf life in international, long distance and cooled condition, plays a key role in global cold chains. Compared with truck transportation, intermodal transportation largely reduces logistics cost and emissions, however, has less flexibility for disturbances. Another aspect is that truck transportation occupies the largest share in inland transportation, which causes traffic congestion and environmental pollutions. Synchromodal transportation is a known method to study the effectiveness, efficiency and sustainability of transportation by using real-time information. However, limited articles can be found about the cold chain perspective, an integral analysis is missing. Our objective is to thoroughly analyze the characteristics and challenges of synchromodal transportation in global cold chains. The critical successful factors are analyzed at first. After that, we survey on planning problems in strategic, tactical and operational level, respectively. Finally, we conclude by suggesting further research directions.

Marine litter in port areas has a huge negative environmental impact and poses a risk to vessels. Therefore port authorities are using special vessels for sweeping. Nowadays, these vessels are usually only deployed after complaints on excessive amounts of marine litter. In this paper an innovative routing method is proposed to sweep marine litter in a port area proactively. The routing method is formulated as a mixed-integer programming (MIP) model. In order to test the sweeping model a dynamic model is developed that predicts the locations in the port area where marine litter will accumulate depending on factors like supply, physical dimensions of port compartments and wind directions. To benchmark the performance of the sweeping model simulations are performed comparing the routing method with other more intuitive policies. It is concluded that using the sweeping policy lower litter levels can be achieved at lower costs.

Nowadays, various railway components are checked by numerous sensors, in workshops and in-service. Railway wheels are critical components, which their health status directly and indirectly are monitored. The Wheel Impact Load Detector (WILD) is a widespread commercial monitoring system, which exploits one or more strain sensors to detect defective wheels using wheel-rail contact force measurement. The objective of the research described in this paper is to use the WILD to measure the wheel diameter. This trait enhances the WILD ability to monitor more features of the wheel condition using the same system. Each wheel has its unique condition along its circumference, which causes a unique pattern of contact force, replicated in every revolution. By having the wheel diameter, the measured impacts can be mapped to the corresponding position over the wheel circumference. To achieve this purpose, a new configuration of strain sensors was proposed and the required algorithm for data filtration and processing was developed. To evaluate this method a set of simulation was carried out and the effect of different parameters such as sensor number, filter threshold, defect size and sensor noise were investigated. As the main result, the capability of the WILD for wheel diameter monitoring was proved.