Modeling and Analysis of Production Systems Operated in a Human-In-The-Loop Fashion

Abstract

Most production systems are operated in a human-in-the-loop fashion, and it is sometimes argued that the human decisions involved make it possible, or at least easier, for the systems to cope with various stationary and nonstationary variations. However, it has not been well-studied and understood how this positive contribution of human decisions work, what factors determine its effect, how the function should be supported or fostered, etc. This paper first briefly reviews conventional production systems simulation techniques and discusses why it is difficult for them alone to address aforementioned questions. This next points to some recent attempts, in production systems engineering and related areas, to study human decisions and their effects by complementally using gaming simulation and agent-based simulation and highlights the potential of combining such behavioral and computational scientific approaches. Then, the paper introduces a cognitive framework model composed of interface, interaction, and incentive dimensions. It can be used for formally characterizing the decisions made by an individual facing a problem situation in operating a production system, and functions as a bond connecting behavioral and computational analyses of the decision maker. The paper further presents some example ongoing research projects worked on by the author’s team in this direction and discusses some future perspective.