Academic articles

A tunnel boring machine (TBM) is the primary resource in a tunnel construction project and generally its advance rate is equal to the performance rate of the whole project. Regarding previous studies, the utilization factor of TBMs is approximately 50% most of the time. The process of repair and maintenance of various parts of the machine and the logistic equipment takes 50% of the time. This case study aims to simulate the whole process of TBM tunneling in Ahwas subway project and find out how different scenarios of repair and maintenance can affect the utilization factor of the TBM. The model is developed using discrete-event simulation (DES) method.

The operation of offshore drilling platforms requires a lot of logistics: supply of platforms by platform supply vessels (PSVs), backward transportation of waste in containers and transportation of oil by tankers to export ports. The severe weather conditions of the Arctic Ocean increase the number of possible disruptions that influence the logistic system. The operation of PSVs and tankers has multiple constraints and interactions. An agent-based simulation has been developed in AnyLogic to support the strategic planning of logistics by year 2042. The presentation discusses the use of the model to determine the required number of vessels and compare different options of crude oil outbound logistic network design.

Many complex real-world problems which are difficult to understand can be solved by discrete or continuous simulation techniques, such as Discrete-Event-Simulation, Agent-Based-Simulation or System Dynamics. In recently published literature, various multilevel and large-scale hybrid simulation examples have been presented that combine different approaches in common environments.

Workers cross-trained with multiple tasks can improve the workforce flexibility for the plant to handle variations in workload. Therefore, it is necessary to study the dynamic multi-skilled workforce planning problem of production line with the application of cross-training method.

In this paper, we present an iterative scheme integrating simulation with an optimization model, for solving complex problems, viz., job shop scheduling. The classical job shop scheduling problem which is NP-Hard, has often been modelled as Mixed-Integer Programming (MIP) model and solved using exact algorithms (for example, branch-and-bound and branch-and-cut) or using meta-heuristics (for example, Genetic Algorithm, Particle Swarm Optimization and Simulated Annealing).

Recargo has been developing an agent-based model with the AnyLogic tool to help us simulate the charging patterns of electric vehicle drivers in California. Our goal is to better understand the potential value from delivering electricity grid services with these vehicles. Development has only been underway for a few weeks, but in that time we’ve been able to use AnyLogic’s accessible interface and Java coding tools to quickly build and test a proof-of-concept model with which we can explore the potential for a more sophisticated and complex effort.

This paper presents an online simulation framework that can be used to support operational decisions within the context of Through-life Engineering Services. Acting as a closed-loop feedback control mechanism, the simulation model is physically coupled to the assets and will be triggered and automatically executed to assess a set of operational decisions related to maintenance scheduling, resource allocation, spare parts inventory etc. Experimental cases comparing the online simulation against the traditional approach will also be presented. The outcomes have demonstrated the prospects of the framework in enabling more effective/efficient operations of engineering services leading to high assets availability and reduced through-life costs.

This paper presents an agent-based model for simulating wind power systems on multiple time scales. The aim is to generate a flexible model that allows us to simulate the output of a wind farm. The model is developed using multiparadigm modelling, combining different approaches such as agent-based modelling, discrete events and dynamic systems.

Looking for new improvement options such as new dispatching rules of an existing semiconductor fabrication facility, a detailed model is indispensable to check the data quality as well as detecting main influences of the facility and finally testing the new optimization approaches.

Contemporary aerospace programmes often suffer from large cost overruns, delivery delays and inferior product quality. This is caused in part by poor predictive quality of the early design phase processes with regards to the operational environment of a product. This paper develops the idea of a generic operational simulation that can help designers to rigorously analyse and test their early product concepts. The simulation focusses on civil Unmanned Air Vehicle products and missions to keep the scope of work tractable.