This monograph contains some ofthe papers presented at a UK-Japanese Workshop on Stochastic Modelling in Innovative Manufacturing held at Churchill College, Cambridge on July 20 and 21st 1995, sponsored jointly by the UK Engineering and Physical Science Research Council and the British Council. Attending were 19 UK and 24 Japanese delegates representing 28 institutions. The aim of the workshop was to discuss the modelling work being done by researchers in both countries on the new activities and challenges occurring in manufacturing. These challenges have arisen because of the increasingly uncertain environment of modern manufacturing due to the commercial need to respond more quickly to customers demands, and the move to just-in-time manufacturing and flexible manufacturing systems and the increasing requirements for quality. As well as time pressure, the increasing importance of the quality of the products, the need to hold the minimum stock of components, and the importance of reliable production systems has meant that manufacturers need to design production systems that perform well in randomly varying conditions and that their operating procedures can respond to changes in conditions and requirements. This has increased the need to understand how manufacturing systems work in the random environments, and so emphasised the importance of stochastic models of such systems.
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This volume contains selected papers presented at a UK-Japanese Workshop held at Churchill College, Cambridge, July 1995. The first group of papers looks at modelling, and solution techniques that have proved useful in the operational and strategic levels of manufacturing-greedy algorithms, Markov Decision processes and Petri Nets. Further papers concentrate on operational aspects of manufacturing in an uncertain environment. The last group describes interesting problems. The volume shows that the need for stochastic modelling is an important factor in support of decision making, and that this is a growing, exciting and rewarding area of research.
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