Title: Optimal vehicle batching and sequencing to reduce energy consumption and atmospheric emissions in automotive paint shops

Authors: Junwen Wang, Jingshan Li, Ningjian Huang

Addresses: Department of Industrial and Systems Engineering, University of Wisconsin – Madison, Madison, WI 53706, USA. ' Department of Industrial and Systems Engineering, University of Wisconsin – Madison, Madison, WI 53706, USA. ' Manufacturing Systems Research Lab., General Motors Research and Development Centre, Warren, MI 48090-9055, USA

Abstract: Reducing energy consumption and carbon emissions is an important issue to achieve sustainable manufacturing. In automotive assembly plants, the largest amount of energy consumption and atmospheric emissions is in paint shop. Optimising the energy usage to pursue maximum energy savings, and reducing carbon dioxide equivalent emissions are of significant importance in automotive paint shops. Instead of inventing new chemicals, new painting processes or new control systems in painting booths and ovens, our research focuses on developing an optimal batch and scheduling procedure of vehicles to achieve the goal of energy and emission reduction. Specifically, by selecting appropriate batch and sequence policies, the paint quality can be improved and repaints can be reduced so that fewer material and energy will be consumed, and less atmospheric emissions will be generated. It is shown that such scheduling and control method can lead to significant energy savings and emission reduction with no extra investment, nor changes to existing painting processes.

Keywords: automotive paint shops; energy consumption; carbon emissions; CO2; sustainable manufacturing; vehicle batching; vehicle sequencing; automobile industry; optimisation; optimal batch policy; optimal scheduling; vehicle painting; sustainability.

DOI: 10.1504/IJSM.2011.042149

International Journal of Sustainable Manufacturing, 2011 Vol.2 No.2/3, pp.141 - 160

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 29 Aug 2011 *

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