Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

Abstract

This paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing system is modelled as a set of interacting resources and queues. At any moment in time, the combined specific states of the resources and queues define the overall state of the manufacturing system. The main contribution of this paper is a set of dynamic complexity measures that quantify the rate at which information is generated by the facility, and which may be applied with or without reference to the facility's schedule. A worked example demonstrates the step-by-step calculations to obtain values of the complexity measures, and guidance is provided on how to obtain the data needed to carry out the calculations. The links between these complexity measures and the behaviour of a facility are identified and described.

Keywords:

• manufacturing systems
• job shops
• manufacturing cells
• cell-based layouts
• complexity
• information theory

Acknowledgements

The authors gratefully acknowledge the support of EPSRC through grants GR/M57842 and GR/L09295. The authors also gratefully acknowledge the support of their academic colleagues especially Gerry Frizelle, Suja Sivadasan, Stella Kariuki, and John Schirn, and of industrial collaborators, such as BAE Systems, Unilever, ALPLA, and Graphic.