Towards an Agent-based Simulation Tool for Manufacturing Systems

Ruiz, Nancy; Giret, Adriana; Botti, Vicente

doi:10.1109/etfa.2006.355417

Cited by 10 publications

(7 citation statements)

References 29 publications

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“…Ingalls [42] and Hicks [43] have emphasized for a hybrid optimization and simulation approach for strategic supply chain planning as this eliminates random trial and error method to obtain potential solutions. Ruiz et al [44] presented a classification of commercial simulation packages with their features and reported that meta-heuristics methods such as GA, tabu search, simulated annealing, and scatter search are commonly used to optimize the configuration decisions in simulation models. Jafferali et al [45] compared the optimization tools available in commercial simulation packages for scheduling.…”

Section: Supply Chain Simulationmentioning

confidence: 99%

Multi-objective supply chain sourcing strategy design under risk using PSO and simulation

Venkatesan

Kumanan

2011

Int J Adv Manuf Technol

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Sourcing strategy design in a supply chain is vital to gain competitive advantage. In recent years, supply chain risks are growing significantly and supplier failure is identified as one of the top supply chain risks. Researchers attempt to mitigate the negative impacts of supplier failure by applying strategies such as local versus global sourcing, single versus dual/multiple-sourcing, performance-based supply contracts, and optimizing the order allocation among suppliers. Global sourcing is a widely recognized strategy among firms, and it involves a trade-off between reliable, high-cost local suppliers and unreliable, low-cost offshore suppliers. The global sourcing is associated with the risks of exchange rate volatility, trade restrictions, longer lead time, and problems with supplier reliability. Sourcing strategy design considering price, exchange rate risks, and supplier delivery reliability is an important research topic and needs attention. In this work, a hybrid optimization and simulation approach is proposed to design the supply chain sourcing strategy. In the optimization approach, a multi-objective binary particle swarm algorithm is developed for minimizing the total cost and maximizing the supplier delivery reliability. Selected scenarios from the optimization results are modeled using Witness simulation software to evaluate the robustness of sourcing strategies under price, exchange rate and demand risks. The proposed approach is exemplified using a real-life case study of a plastic product manufacture in India.

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Section: Supply Chain Simulationmentioning

confidence: 99%

Multi-objective supply chain sourcing strategy design under risk using PSO and simulation

Venkatesan

Kumanan

2011

Int J Adv Manuf Technol

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“…The lack of awareness about the potential of agent technology, concerns regarding MAS stability, scalability and survivability as well as missing standards, design and development tools have been seen as major obstacles that have to be overcome in order to achieve progress in the adoption of agent technologies [13]. Simulation is considered as effective method for testing different control architectures and improving the quality of solutions, which are in many cases closely related to control systems and scenarios in real life manufacturing [14].…”

Section: B Mas In Production Automationmentioning

confidence: 99%

A Pattern-Based Coordination and Test Framework for Multi-Agent Simulation of Production Automation Systems

Moser

Merdan

Biffl

2010

2010 International Conference on Complex, Intelligent and Software Intensive Systems

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Production automation systems consist of many entities (like robots and shuttles) that interact in complex ways to provide the overall system functionality like product assembly. Multi-Agent Systems (MAS) can simulate these system entities and their interactions to better understand the system behavior according to production strategies and system configuration, which are otherwise hard to determine before their (costly) implementation. A main challenge is to coordinate the groups of agents effectively to reach a common production goal, e.g., fast and robust delivery on customer orders for assembling a set of products. In this paper, we introduce the pattern-based extension of the MAS-based manufacturing agent simulation tool (MAST) to support the simulation and evaluation of business processes in an assembly workshop: a layered coordination and test framework has been implemented and evaluated in cooperation with industry partners. Domain experts found the coordination patterns usable and useful to elicit their knowledge. The test framework allowed exploring the effects of production strategies on the system 30 times faster than with a real-world hardware workshop.

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“…This paper presents an extension of a previous work (Ruiz et al, 2006) in which a brief study was made to identify the manufacturing simulation process. The study distinguished two main phases in the simulation process of a manufacturing system: Model Creation and Model Simulation.…”

Section: A Mas Based Simulation Toolmentioning

confidence: 99%

Holonic Architecture for a Multiagent-Based Simulation Tool

Ruiz¹,

Giret²,

Botti³

2007

Proceedings of the Ninth International Conference on Enterprise Information Systems

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In the last few years Holonic Manufacturing Systems (HMS) have been used to improve some areas such as control systems of manufacturing systems, monitoring and diagnosis systems, and Computer Integrated Manufacturing architectures. This paper presents an application of the holonic approach together with the Multi-agent Systems (MAS) to develop a Simulation Tool for manufacturing systems. The architecture for this tool is related to functionalities that support the Manufacturing Model created by the User. This proposal allows the User to take advantage of these two approaches to simulate a manufacturing environment according to the manufacturing requirements.

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Towards an Agent-based Simulation Tool for Manufacturing Systems

Cited by 10 publications

References 29 publications

Multi-objective supply chain sourcing strategy design under risk using PSO and simulation

Multi-objective supply chain sourcing strategy design under risk using PSO and simulation

A Pattern-Based Coordination and Test Framework for Multi-Agent Simulation of Production Automation Systems

Holonic Architecture for a Multiagent-Based Simulation Tool

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