Bayesian Petri net based framework for performance analysis and control of manufacturing systems
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abstract
The paper presents a control and performance analysis framework by integrating Bayesian model selection and stochastic Petri nets. Petri net based control architecture provides strong basis for understanding key manufacturing control issues and to obtain performance measures such as throughput and machine utilization. A Bayesian framework is integrated with Petri net model to identify input distributions and update these distributions in light of new data. The Bayesian Petri net based approach thus provides a strong control and analysis framework which helps in identifying underlying control issues and provides bayesian simulation platform for accurate prediction and monitoring of performance measures.
