# An-Najah National University

• Wednesday, January 1, 2003
• New manufacturing modeling methodology: deterministic and stochastic dynamic modeling of continuous manufacturing systems using analogies to electrical systems
• Published at:Proceedings of the 35th conference on Winter simulation: driving innovation, Pages: 1134 - 1142, 2003
• A dynamic system model of continuous manufacturing systems has been developed based on analogies with electrical systems. This model has the capability to model both deterministic and stochastic systems. The model provides physically meaningful governing equations to describe both the steady state and transient responses of continuous manufacturing systems. For stochastic solutions, the model is not limited to any specific probabilistic distribution. The model is demonstrated by application to a representative continuous manufacturing line for both deterministic and stochastic cases. The results of the stochastic case are compared to those from a discrete event simulation tool using a paired t-test at the 95% confidence level. For some results, the difference is statistically insignificant. For others, there is a statistically significant difference. However, in both cases the percentage difference is within a reasonable range.
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• Wednesday, January 1, 2003
• Deterministic and stochastic dynamic modeling of continuous manufacturing systems using analogies to electrical systems
• Published at:Simulation Conference, 2003. Proceedings of the 2003 Winter, Volume: 2, On page(s): 1134- 1142 vol.2
• A dynamic system model of continuous manufacturing systems has been developed based on analogies with electrical systems. This model has the capability to model both deterministic and stochastic systems. The model provides physically meaningful governing equations to describe both the steady state and transient responses of continuous manufacturing systems. For stochastic solutions, the model is not limited to any specific probabilistic distribution. The model is demonstrated by application to a representative continuous manufacturing line for both deterministic and stochastic cases. The results of the stochastic case are compared to those from a discrete event simulation tool using a paired t-test at the 95% confidence level. For some results, the difference is statistically insignificant. For others, there is a statistically significant difference. However, in both cases the percentage difference is within a reasonable range.
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