Abstract
Lean production is a set of methods aimed at increasing efficiency and flexibility within a firm by eliminating waste and accurately defining value. For this reason, it is interested in eliminating activities that do not add value to the product to reduce costs. Within the scope of lean production, different methods are used based on certain priorities and simultaneously. In this study, the Lean Production Leveling-Heijunka approach, a lean production method applied in a mold sponge manufacturing firm, is discussed. In the accessible literature, it has been seen that the heijunka method has been studied little before and no linear model has been found for its application. Therefore, within the scope of this study, a multi-objective linear model that includes production leveling, sequencing and job stability elements is proposed. As the proposed model is multi-objective, the weighted sum method was used as the aim aggregation method to solve it. The problem of the firm was solved using the proposed model in GAMS/CPLEX. To evaluate the performance of the model, first a small-size sample problem was solved and then the main problem of the firm where the application was used was solved. The effectiveness of the model was evaluated by comparing the results obtained after solving the firm problem with the current case. In addition, Heijunka values for both cases were calculated to demonstrate the success of the proposed model's solution. According to the calculations, the Heijunka ratio was four in the solution obtained by applying the proposed model, while it was two in the current situation. These results demonstrate that a successful Heijunka method was implemented in the firm where the application was conducted, and the production process was made more balanced.
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Tutumlu, B., Baş, S. A., & Kocakalay, Ş. (2024). Multi-objective programming approach for production leveling problem: An automotive sub-industry example. Journal of the Faculty of Engineering and Architecture of Gazi University, 40(1), 1–10. https://doi.org/10.17341/gazimmfd.1341993
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