SUMMARY This paper presents a control methodology for flow shops that is decentralized and adaptive in nature, and has low data handling and computational requirements. The methodology is based on stochastic automata methods for modelling learning behaviour. It is proposed that such a methodology can be used with Kanban type control technique to make flow shop systems more flexible and adaptive in nature, Relationship of the control model to computational models such as neural computing is discussed.
No takes yet. Share an insight, caveat, or question.
Chaudhury et al. (1990) studied this question.
Synapse has enriched one closely related paper. Consider it for comparative context: