Abstract
The paper presents the approach to the car buffering problem in the paint shop from the perspective of modern industrial plant requirements. The control of buffering process is connected with sequencing problem. A sequence, in which car bodies are painted is particularly important, because the minimization of the number of painting guns changeovers results in minimizing production costs. The problem of car sequencing has been widely considered in the literature. However, a large number of assumptions and simplifications, made by the researchers, make it impossible to apply developed solutions in practice. The paper considers the car sequencing issue taking into account problems that occur on the production line in the real paint shop. After presenting the algorithm, used in the analyzed plant, four sequencing algorithms, used to define the output sequence from the buffer, are discussed. Two algorithms are modifications of the well known scheduling heuristics – that are SPT and LPT methods. Based on these rules and follow-up control idea two new algorithms are proposed. The input sequence is determined in one of two ways. The correctness of the car body buffer control in the paint shop was verified in the test carried out using innovative method – virtual commissioning. The aim of the research was to identify the most effective methods that will be developed in the future. During tests, the buffer flow was monitored in order to identify unfavorable buffering situations deemed unacceptable in real conditions. The most unfavorable cases are presented and discussed in the article.
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References
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Acknowledgement
This work has been supported by Polish Ministry of Science and Higher Education under internal grants BK-204/RAu1/2017 and BKM-508/RAu1/2017 for Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland and by the company ProPoint Sp. z o.o. Sp. k.
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Alszer, S., Krystek, J., Bysko, S. (2018). Complex Approach to the Control of Car Body Buffering in the Paint Shop. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2018. AUTOMATION 2018. Advances in Intelligent Systems and Computing, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-319-77179-3_14
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