journal article
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Wild, Rosemary H.; Pignatiello, Joseph J.
doi: 10.1177/003754979105700603pmid: N/A
Well designed experiments can dramatically improve the statistical accuracy of simula tion output data and facilitate the statistical analysis. In this paper we propose an experimental design strategy for designing robust systems using discrete-event simulation. The proposed strategy is motivated by Genichi Taguchi's strategy for improving product and process quality in manufacturing. Robust systems are systems that not only satisfy performance criteria, but also are not sensitive to uncontrollable environmental conditions or noise in the system's environment. We demonstrate the proposed experimental design strategy with a jobshop example and discuss the potential benefits of employing such a strategy for designing robust systems in general.
Clymer, John R.; Hernandez, Daniel
doi: 10.1177/003754979105700606pmid: N/A
Distributed simulation based on Opera tional Evaluation Modeling (OpEM) is discussed. OpEM, a system design and analysis methodology, uses a two-dimen sional, directed graph language to describe system operation. The OpEM simulation programming system, that implements this methodology, includes object-oriented event processing routines, moving-object routines, an expert system controller, and continuous system simulation routines. These routines are required to model large systems, such as the Strategic Defense Initiative (SDI) systems, that are characterized by closely coupled, context sensitive interactions. These interactions are modeled using a large global state space consisting of both discrete and continuous state variables. Execution of such large, complex models on uniprocessors can be slow; therefore, possible speedup by execution on a multiprocessor system, a set of processors that share memory, is investigated. A generic surface- ship warfare simulation, characteristic of many large models, is executed on a simulation of a multiprocessor system to investigate speedup.
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