Introduction to military training simulation: a guide for discrete event simulationists
Proceedings of the 30th conference on Winter simulation
Simulation in the supply chain context: a survey
Computers in Industry
Feature-based survey of model transformation approaches
IBM Systems Journal - Model-driven software development
Simulation Modeling and Analysis with Expertfit Software
Simulation Modeling and Analysis with Expertfit Software
System modeling in sysml and system analysis in arena
Proceedings of the Winter Simulation Conference
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Discrete-event simulation (DES) is used to evaluate alternative resource configurations and production operation plans and schedules in the manufacturing environment. However, benefits from using simulation to guide these decisions has to be weighed against the time and cost usually required to create and exercise the simulations. Where such decisions are taken frequently, a common practice is to create a simulator which accommodates the typical production alternatives, and link it to an Excel-database for specifying the scenario and displaying the simulation results. This is an effective approach when the simulator can be reused with sufficient frequency, but it suffers from several deficiencies. It can be difficult to maintain the simulator in conformance with the actual production capabilities (changing products, changing processes, etc). Knowledge about the production process is captured in the simulator and in the Excel-database, neither of which is a particularly effective knowledge sharing platform. We propose an alternative model-driven approach that automates the creation of DES models from SysML models specified using domain-specific semantics. Our approach enables domain stakeholders to define the problem in its own terms, and eliminates manual simulation model coding. In an industrial case study, we have used Arena™ as the DES platform and created a domain specific language (DSL) for electronics assembly. Not only is knowledge about production captured in a form that is accessible by all the stakeholders, the time and cost for simulation analysis is reduced by an order of magnitude.