Phillip A. Farrington

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This paper further develops some of the ideas set out by Cheng (1998) for output analysis using Bayesian Markov Chain Monte Carlo (MCMC) techniques, when a regression metamodel is to be fitted to simulation output. The particular situation addressed by Cheng was where there is uncertainty about the number of parameters needed to specify a model. This arises(More)
Simulation experiments can benefit from proper planning and design, which can often increase the precision of estimates and strengthen confidence in conclusions drawn from the simulations. While simulation experiments are broadly similar to any statistical experiment , there are a number of differences. In particular , it is often possible to exploit the(More)
This paper presents an overview of a simulation environment used for rapid modeling of electronics manufacturing lines. This environment, the Electronics Manufacturing Simulator (EMS), consists of a line definer and a static analyzer. Included in this paper are a description of the EMS, an application of the EMS, and a discussion of results of the(More)
This paper presents a conceptual framework for simulation modeling which emphasizes model reusability. Reusability is achieved through the provision of separate modeling constructs for physical, information, and control/decision elements of a system. These constructs contribute to a modular environment in which the modeling elements, once created, can be(More)
This paper describes the research efforts in the Center for Computer Integrated Manufacturing at the Oklahoma State University to develop an object-oriented modeling environment. After providing the underlying motivation for the research effort, some of the major research tasks are described. Highlights of this development effort are: physical and(More)