Paint Shop Scheduling in the Automotive Supply Industry

Abstract

We formulate and present a production scheduling problem that appears in paint shops of the automotive supply industry. The goal is to find an optimized schedule for the painting of a large number of different synthetic material pieces that will later be used as assembly parts during car manufacturing. During the process of painting, the demanded pieces will be placed on special made carrier devices which automatically move through the paint shop on a system of conveyer belts and pass by multiple cabins that will then apply layers of paint onto the pieces. Finding a good painting schedule therefore includes the determination of an efficient distribution of the demanded pieces onto the carrier devices and deciding on an optimized production sequence. Thereby, the main optimization objective is to minimize the setup costs that are caused by color and carrier changes that appear within the painting sequence. We formulate the problem mathematically and also propose heuristic solution strategies. Furthermore, we provide a collection of instances and evaluate the results produced with the proposed solution methods. Affiliation: Christian Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling, TU Wien Acknowledgements: The financial support by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development is gratefully acknowledged.

We formulate and present a production scheduling problem that appears in paint shops of the automotive supply industry. The goal is to find an optimized schedule for the painting of a large number of different synthetic material pieces that will later be used as assembly parts during car manufacturing. During the process of painting, the demanded pieces will be placed on special made carrier devices which automatically move through the paint shop on a system of conveyer belts and pass by multiple cabins that will then apply layers of paint onto the pieces. Finding a good painting schedule therefore includes the determination of an efficient distribution of the demanded pieces onto the carrier devices and deciding on an optimized production sequence. Thereby, the main optimization objective is to minimize the setup costs that are caused by color and carrier changes that appear within the painting sequence. We formulate the problem mathematically and also propose heuristic solution strategies. Furthermore, we provide a collection of instances and evaluate the results produced with the proposed solution methods. Affiliation: Christian Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling, TU Wien Acknowledgements: The financial support by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development is gratefully acknowledged.