4.7 Article

Modelling and numerical analysis for seru system balancing with lot splitting

Journal

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 61, Issue 21, Pages 7410-7433

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2022.2149873

Keywords

Seru production; scheduling; lot splitting; multi-objective optimisation; NSGA-II

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This study investigates a multi-objective model for line-cell conversion with lot splitting in seru production, and develops an improved algorithm to solve it. Extensive numerical simulations and comparisons with other algorithms demonstrate the effectiveness and efficiency of lot splitting in improving system balancing and reducing makespan. Sensitivity analysis provides insights into the contribution of model parameters towards the objectives, offering management implications for seru production decision-making in enterprises.
Lot splitting is one of the effective technologies of time-based strategy and has been widely studied in a variety of production environments. Nevertheless, the literature on its application in seru production has been highly scarce until now. Seru system is composed of simple equipment and multi-skilled workers, which can be quickly converted from the traditional assembly line to seru units. As an innovative production mode, seru production inevitably allows applying lot splitting in the real world. Therefore, a multi-objective model is studied for line-cell conversion with lot splitting, aiming at determining the trade-off among makespan, inter-seru system balancing, and intra-seru system balancing. Due to the proposed model's NP-hard nature, an improved NSGA-II was developed to solve it. Finally, extensive numerical simulations are conducted. Compared to no lot splitting, lot splitting is improved by 4.2% and 3.7% in terms of inter-seru system balancing and makespan respectively. The better efficiency and effectiveness of the improved NSGA-II are proved by comparisons with other state-of-the-art algorithms. Additionally, a sensitivity analysis is conducted to ascertain the degree of contribution of the model parameters towards the value of objectives, which provides management implications to support the decision-making of seru production for the enterprise.

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