Optimizing real-time vehicle sequencing of a paint shop conveyor system

• We develop a simulation model of a paint shop at the GM plant in Arlington, Texas.
• We formulate a dynamic program for merging vehicle batches of different colors.
• We formulate an integer program for splitting vehicle batches of different colors.
• We conduct simulation experiments evaluating these algorithms at the GM plant.
• We conduct simulation experiments to determine optimal vehicle batch sizes.

A discrete event simulation model and a decision optimizer that were developed for a General Motors paint shop conveyor system are presented. The simulation model interacts with the decision optimizer at four critical points in the system, trying to regroup batches of different colored vehicles. The decision optimizer employs dynamic programming and integer programming to optimize vehicle routing policies. Simulation results of the current decision making policies are compared with those of the proposed optimized policies showing that the number of paint head changes can be significantly reduced resulting in substantial savings on paint head cleaners and paint.