Abstract
With the rise of Industry 4.0 an era of real-time global connectivity between customers and the processes that transform consumer goods is imminent. Faced with the need to satisfy the current dynamic demand, the Japanese technology industry has developed an innovative production system called seru, which is distinguished by its satisfactory results in economic and environmental terms. This study poses a production planning problem in a seru production system considering heterogeneous workers and the energy consumption of production. To solve it, a multi-objective mathematical model is proposed in order to balance the production time between workers (intra-seru) and between serus (inter-seru) and minimize the total energy consumption. For larger instances, a metaheuristic algorithm is developed based on the evolutionary algorithm NSGA-II. Finally, the effectiveness of the proposed genetic algorithm is evaluated by comparing the area under the curve obtained with the solutions of the pareto frontier that it generates and the area under the curve from the pareto frontier of the multi-objective linear optimization model created via \(\varepsilon \) - constraint.
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References
Lian, J., Liu, C., Li, W., Yin, Y.: Multi-skilled worker assignment in seru production systems considering worker heterogeneity. Comput. Ind. Eng. 118, 366–382 (2018). https://doi.org/10.1016/j.cie.2018.02.035
Liu, C., Dang, F., Li, W., Lian, J., Evans, S., Yin, Y.: Production planning of multi-stage multi-option seru production systems with sustainable measures. J. Clean. Prod. 105, 285–299 (2014). https://doi.org/10.1016/j.jclepro.2014.03.033
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002). https://doi.org/10.1109/4235.996017
Yin, Y., Stecke, K.E., Swink, M., Kaku, I.: Lessons from seru production on manufacturing competitively in a high cost environment. J. Oper. Manag. 49–51, 67–76 (2017). https://doi.org/10.1016/j.jom.2017.01.003
Liu, C., Stecke, K.E., Lian, J., Yin, Y.: An implementation framework for seru production. Int. Trans. Oper. Res. 21, 1–19 (2014). https://doi.org/10.1111/itor.12014
Bhaskar, K., Srinivasan, G.: Static and dynamic operator allocation problems in cellular manufacturing systems. Int. J. Prod. Res. 35(12), 3467–3482 (1997). https://doi.org/10.1080/002075497194192
Kaku, I.: Is seru a sustainable manufacturing system? Procedia Manuf. 8, 723–730 (2017). https://doi.org/10.1016/j.promfg.2017.02.093
Liu, C.G., Lian, J., Yin, Y., Li, W.J.: Seru Seisan- an innovation of the production management mode in Japan. Asian J. Technol. Innov. 18(2), 89–113 (2010). https://doi.org/10.1080/19761597.2010.9668694
Haimes, Y.: On a bicriterion formulation of the problems of integrated system identification and system optimization. IEEE Trans. Syst. Man Cybern. SMC–1(3), 296–297 (1971). https://doi.org/10.1109/TSMC.1971.4308298
Liu, R., Liu, M., Chu, F., Zheng, F., Chu, C.: Eco-friendly multi-skilled worker assignment and assembly line balancing problem. Comput. Ind. Eng. 151, 106944 (2020). https://doi.org/10.1016/j.cie.2020.106944. ISSN: 0360–8352
Ying, K.C., Tsai, Y.J.: Minimising total cost for training and assigning multiskilled workers in seru production systems. Int. J. Prod. Res. 55(10), 2978–2989 (2017). https://doi.org/10.1080/00207543.2016.1277594
Liu, C., et al.: Training and assignment of multi-skilled workers for implementing seru production systems. Int. J. Adv. Manuf. Technol. 69, 937–959 (2013). https://doi.org/10.1007/s00170-013-5027-5
Yılmaz, O.F.: Operational strategies for seru production system: a bi-objective optimisation model and solution methods. Int. J. Prod. Res. 58(11), 3195–3219 (2020). https://doi.org/10.1080/00207543.2019.1669841
Gen, M., Cheng, R.: Genetic Algorithms and Engineering Optimization. Wiley, Hoboken (1999)
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Escobar Forero, S.M., Amaya Guio, C.A. (2021). Production Planning in a Seru Production System, Considering Heterogeneity to Balance Production Times and Minimize Energy Consumption. In: Rossit, D.A., Tohmé, F., Mejía Delgadillo, G. (eds) Production Research. ICPR-Americas 2020. Communications in Computer and Information Science, vol 1407. Springer, Cham. https://doi.org/10.1007/978-3-030-76307-7_18
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DOI: https://doi.org/10.1007/978-3-030-76307-7_18
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