"Petri Net Based Modeling Framework Coupled With Bayesian Methods For Robust Manufacturing System"
Short Bio:
Manufacturing system design decisions are costly and involve significant investment in terms of allocation of resources. These decisions are complex due to uncertainties related to uncontrollable factors such as processing times and part demands. In order to find a robust design configuration, the designers need accurate methods to model various uncertainties and efficient ways to search for feasible configurations. In this talk, a Petri net based modeling framework coupled with Bayesian methods for robust manufacturing system design is presented. This framework provides a unified platform to model and capture impact of uncertainties on system dynamics and performance. In addition, a multi objective GA based approach is used to search for alternative design configurations against multiple objectives. The proposed approach provides a flexible and accurate way to find a robust manufacturing system design by using a multi objective GA for searching candidate configurations, Bayesian methods for uncertainty representation and Petri nets for accurately modeling manufacturing systems. methods.

Seminar Abstract:
Bikram Sharda is a Ph.D. candidate in Department of Industrial & Systems engineering. He received his Bachelor of Engineering (B.E.) from Thapar Institute, India in 1999 and Master of Science (M.S.) degree from Texas A&M University in 2003. Before joining Texas A&M University in August 2001, he worked as an Industrial engineer in Swaraj engines limited, India from July 1999 until July 2001. His research interests are in the areas of simulation modeling, Petri nets, Heuristic optimization and Bayesian methods.