Simulation optimization of a multi-stage multi-product paint shop line with Response Surface Methodology

Abstract

Recently, Response Surface Methodology (RSM) has attracted a growing interest, along with other simulation optimization (SO) techniques, for non-parametric modeling and robust optimization of systems. In the optimization stage of this study, the authors use RSM to find optimum working conditions of a system. The authors also use discrete event simulation modeling, optimization stage integration, design of experiment (DOE) and sensitivity analysis (a) to investigate the behavior of a real paint shop production line via construction of response surface plots and (b) to reveal the influence of input variables, as well as to determine interaction effects between them. The proposed approach presents an approximation model management structure for the computation-intensive optimization problem of an automotive factory with reduced variance, computational cost and amount of effort.

A meta-model based simulation optimization using hybrid simulation-analytical modeling to increase the productivity in automotive industry

“…The proposed method is applied to an actual system to verify the PLC code in testing that showed the effectiveness of the system. Dengiz and Belgin [7,8] used response surface methodology (RSM) for optimization of a paint shop production line. Moon et al [25] presented a case study of a body shop design using 3D simulation in a Korean automotive factory.…”

“…The paint shop production line that was described by Dengiz and Belgin [7,8] was considered in this study. The production line was re-organized in their study considering only physical constraints of the facility and human resource.…”

“…That is, operation times increase when the number of operators decreases. Paint shop is multi-stage production line with multiple operators [7,8]. Figure 2 shows the flow of this paint shop production system.…”

“…cementing II, priming II, prep for chassis painting, chassis painting, prep for final painting, finalizing chassis painting, final painting, and quality control with workers 11, 14, 7,2,12,3,3,2,9,2,4,3,2,8 respectively for during first two shifts. They are reduced for third shifts as; 7,9,5,2,8,2,2,2,6,2,3,2,2,6 [7,8].…”

“…Due to the defective operation of the buses nearly 25% of them go back for re-paint [7,8]. This triggered the need for a model-based analysis.…”