Clinic: correlated inputs in an automotive paint shop fire risk simulation

Authors:
Debra Elkins;A. Christine LaFleur;Earnest Foster;Jeffrey Tew;Bahar Biller;James R. Wilson
Affiliations:
General Motors R&D Center, Warren, MI;Corporate Risk Management, Russelsheim, Germany;General Motors R&D Center, Warren, MI;General Motors R&D Center, Warren, MI;Carnegie Mellon University, Pittsburgh, PA;North Carolina State University, Raleigh, N.C.
Venue:
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Year:
2007

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Abstract

General Motors (GM) has developed a first proof-of-concept simulation model to explore impacts of various fire events in automotive paint shop operations. The approach uses a chronological event tree structure to assess effectiveness of various fire protection options to reduce the potential for significant property damage and loss of production capability. For confidentiality purposes, GM has disguised the numerical data presented in this case study. GM is seeking advice from the simulation community on modeling questions related to input distribution modeling, and correlation structure among input random variables.