Abstract
The integration of computer simulation with artificial intelligence has recently been regarded by many as the next natural developmental step. It is suggested that knowledge-based simulation models will in future be used extensively for systems design and evaluation. However, there is still much work to be done before these developments can produce successful practical tools for managers and engineers. One major problem of simulation/expert systems integration when applied in a manufacturing environment occurs as a result of the diversity of manufacture. To utilize a knowledge-based approach effectively, the decision process must be sufficiently limited in variety. This in turn requires that particular measures of effectiveness be devised that are not too diversified for expert system applications. It is therefore necessary to identify the key process parameters and performance indicators related to certain common key features shared between a relatively wide range of systems. Based on a detailed analysis of the production cost structure of a manufacturing system, an attempt to develop a measure of system effectiveness based on one such feature is reported.
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