Gabriel Lodewijks

Simulation of a multiterminal system for container handling

A generic simulation model structure for the design and evaluation of multiterminal systems for container handling is proposed. A model is constructed by combining three basic functions: transport, transfer, and stacking. It can be used for further detailing of the subsystems in the terminal complex while preserving the container flow patterns in the system. The modeling approach has been applied to the complete set of existing and future terminals in the Rotterdam port area, using forecasts of containers flows, statistical data from existing terminals, expert opinions, and conceptual designs of the new port area called “second Maasvlakte”. Experimental results including the requirements for deep-sea quay lengths, storage capacities, and equipment for interterminal transport are shown. Further traffic flows on the terminal infrastructure are determined, and the consequences of applying security scanning of containers are evaluated.

Comparison of routing strategies for AGV systems using simulation

In automated transport systems, the origin-destination combinations are normally connected through a fixed layout, not representing the shortest path. The flexibility of these systems is limited and often the infrastructure is not optimally used. With the introduction of more powerful onboard computers and advanced sensor technology, the positioning and navigating possibilities of AGVs increased. However the routes, although virtual, are still fixed. A new step ahead would be to determine each path dynamically. This would use the free ranging capacities of AGVs to its full potential. In this paper, the benefits of the dynamic free ranging approach are investigated; a simulation model on the strategic level is presented that compares several common fixed layouts with the shortest connection approach. Naturally, the avoidance of collisions plays a central role. It is concluded that dynamic free ranging has high potential in terms of transport capacity of the resulting system

Damp trend Grey Model forecasting method for airline industry

This paper presents a modification of the Grey Model (GM) to forecast routes passenger demand growth in the air transportation industry. Forecast methods like Holt-Winters, autoregressive models, exponential smoothing, neural network, fuzzy logic, GM model calculate very high airlines routes pax growth. For this reason, a modification has been done to the GM model to damp trend calculations as time grows. The simulation results show that the modified GM model reduces the model exponential estimations grow. It allows the GM model to forecast reasonable routes passenger demand for long lead-times forecasts. It makes this model an option to calculate airlines routes pax flow when few data points are available. The United States domestic air transport market data are used to compare the performance of the GM model with the proposed model.

Improving travel time reliability by the use of trip booking

The congestion of our infrastructure, particularly urban roads, continues to increase. Efficient planning, for instance in freight transport, is hindered by the resulting unreliability of travel times. Another effect of this congestion is a reduced utilization rate of the road. This paper presents Trip Booking, a method aimed at improvement of the reliability of travel times as well as an increase in the effective use of road capacity. Increased reliability facilitates better logistic planning. It furthermore allows sharing of infrastructure between different modalities, with each modality having its own operational time window. The system aims at open dedicated infrastructure such as bus lanes and dedicated freight lanes and preserves autonomy of both the provider and the user of the infrastructure. The advantage claims are supported by simulation results for basic network configurations.

A Methodology to Predict Power Savings of Troughed Belt Conveyors by Speed Control

Conventional troughed belt conveyors often receive material flows that are smaller than their conveying capacity. DIN 22101 indicates that reducing the belt speed, and thereby maximizing belt load, always results in a reduction of the required mechanical and electrical drive power. Predictions of the speed control savings by DIN22101, however, are inaccurate. Therefore power consumption savings can be truly validated only by physical measurements. Several measurements were carried out for validation purposes. With information on speed control savings an evaluation can be made whether the capital expenditures required for speed control conversion are economically feasible. This article provides a methodology to predict these savings with the use of DIN 22101.

The application of distributed simulation in TOMAS: redesigning a complex transportation model

This paper describes the application of distributed discrete event simulation in the study of an automated container terminal. The new model was developed to continue the study of large and complex logistic systems. In a previous study, a standalone model of the terminal was used that included all the characteristics of container handling between the ships and the container stack. A new distributed simulation model was developed by decomposing the original model into a distributed structure of communicating, small sub models. It is shown that with relatively little effort and hardly any programming overhead, a complex standalone model can be decomposed into small, easy to understand sub models. The new distributed structure improves the transparency and maintainability of the simulation model, while guaranteeing the original benefits of the standalone model and the required reproducibility of the experiments.

Reliability of RFID in Logistic Systems

The objective of this research work is to investigate the reliability of RFID in logistics systems. Starting from a general introduction of passive UHF RFID systems, the application of these systems in logistic systems and the technical challenges that are faced during application are discussed. Based on these discussions the set-up of RFID performance test is discussed and performance indicators are given. Finally typical results of readability tests are presented and conclusions are drawn on how to determine the reliability of the application of RFID systems in logistic systems

A Novel Embedded Conductive Detection System for Intelligent Conveyor Belt Monitoring

Continuous transport systems such as belt conveyor systems are playing an important role nowadays in industrial fields of logistics, transportation, storage, etc. Condition monitoring has been an established tool and widely applied to transportation management systems. However intelligent monitoring of belt conveyor systems is still in an early stage. This paper introduces an embedded conductive detection (ECD) technology that uses a magnet matrix embedded into the conveyor belt carcass and outside sensors to detect and monitor most of the conveyor belt parameters simultaneously. As a novel nondestructive test (NDT) technology, it overcomes drawbacks of traditional conveyor belt monitoring technologies and it has characteristics of absolutely maintenance free, long lifetime, non-contact monitoring and passive measurement. In this paper, applications of the main principle of the ECD technology have also been extended to the field of automatic guided vehicles (AGVs)

Dynamic Free Range Routing for Automated Guided Vehicles

In this paper an algorithm is presented that allows for dynamic free range route planning for automated guided vehicles (AGVs). This routing algorithm is based on the route choice methodology from a microscopic pedestrian behavioral model. Until now, AGVs use a map of predefined, fixed paths that are combined to obtain routes along which they move from origin to destination point. Although it allows for reliable and safe automation of vehicles with limited maneuverability, the use of fixed paths leads to unnecessary long routes, congestion, deadlocks and makes the routing system vulnerable to disruptions at the level of route execution. The developed routing algorithm dynamically determines free ranging trajectories that are optimized regarding arrival time while avoiding static obstacles and collisions with other AGVs

Trajectory tracking of autonomous vessels using model predictive control

Abstract Autonomous surface vehicles are with increasing popularity being seen in various applications where automatic control plays an important role. In this paper the problem of two-dimensional trajectory tracking for autonomous marine surface vehicles is addressed using Model Predictive Control (MPC). At each time step, the reference trajectories of a vessel are assumed to be known over a finite time horizon; the MPC controller computes the optimal forces and moment the vessel needs in order to track the trajectory in an optimal way Based on a horizontal 3 degrees of freedom nonlinear scaled vessel model, we present both nonlinear MPC (NMPC), which solves a constrained multi-variable nonlinear programming problem, and linearized MPC (LMPC), which solves a constrained quadratic programming problem through on-line iterative optimization. In the latter case, the model used in LMPC for prediction is obtained from a successive linearization of the nonlinear vessel model. Comparisons on performance and computational complexity of the two approaches are presented. The effectiveness of the MPC formulations in vessel trajectory tracking, especially the ability of explicitly handling constraints, is demonstrated via simulations.