Abstract
Industry 4.0 (I4.0) has enabled a high development potential in the optimisation of production planning and control problems. This article is a preliminary analysis of the existing scientific literature on planning and management problems, specifically in the production, operations and scheduling areas. This review delves into sustainability concepts and perspectives towards Industry 5.0 (I5.0) that appear in the existing literature. A classification of the reviewed articles is presented. It is based on the following concepts: research methodology, modelling approach, lean approach and resolution approach, problem type and subtype, and I5.0 and sustainability integration into the literature. Finally, the main research gaps, challenges and trends for future research are identified.
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References
Amjad, M.S., Rafique, M.Z., Khan, M.A.: Leveraging optimized and cleaner production through industry 4.0. Sustain. Prod. Consum. 26, 859–871 (2021). https://doi.org/10.1016/j.spc.2021.01.001
Bartol, T., Budimir, G., Dekleva-Smrekar, D., Pusnik, M., Juznic, P.: Assessment of research fields in Scopus and Web of Science in the view of national research evaluation in Slovenia. Scientometrics 98(2), 1491–1504 (2014). https://doi.org/10.1007/S11192-013-1148-8
Battini, D., Berti, N., Finco, S., Zennaro, I., Das, A.: Towards industry 5.0: a multi-objective job rotation model for an inclusive workforce. Int. J. Prod. Econ. 250, 108619 (2022). https://doi.org/10.1016/j.ijpe.2022.108619
Groten, M., Gallego-García, S.: A systematic improvement model to optimize production systems within industry 4.0 environments: a simulation case study. Appl. Sci. 11(23), 11112 (2021). https://doi.org/10.3390/app112311112
Khettabi, I., Benyoucef, L., Boutiche, M.A.: Sustainable multi-objective process planning in reconfigurable manufacturing environment: adapted new dynamic NSGA-II vs New NSGA-III. Int. J. Prod. Res. 60(20), 6329–6349 (2022). https://doi.org/10.1080/00207543.2022.2044537
Kumar, R., Singh, S.P., Lamba, K.: Sustainable robust layout using Big Data approach: a key towards industry 4.0. J. Cleaner Prod. 204, 643–659 (2018). https://doi.org/10.1016/j.jclepro.2018.08.327
Li, J., Tan, X., Li, J., Caselli, F.: Research on dynamic facility layout problem of manufacturing unit considering human factors. Math. Probl. Eng. 2018(1992725078), 13 (2018). https://doi.org/10.1155/2018/6040561
Li, M., Huang, G.Q.: Production-intralogistics synchronization of industry 4.0 flexible assembly lines under graduation intelligent manufacturing system. Int. J. Prod. Econ. 241, 108272 (2021). https://doi.org/10.1016/j.ijpe.2021.108272
Li, Y., Carabelli, S., Fadda, E., Manerba, D., Tadei, R., Terzo, O.: Machine learning and optimization for production rescheduling in Industry 4.0. Int. J. Adv. Manuf. Technol. 110(9–10), 2445–2463 (2020). https://doi.org/10.1007/s00170-020-05850-5
Ming-Liang, L.: An algorithm for arranging operators to balance assembly lines and reduce operator training time. Appl. Sci. 11(18), 8544 (2021). https://doi.org/10.3390/app11188544
Mula, J., Bogataj, M.: OR in the industrial engineering of Industry 4.0: experiences from the Iberian Peninsula mirrored in CJOR. CEJOR 29(4), 1163–1184 (2021). https://doi.org/10.1007/s10100-021-00740-x
Rácz-Szabó, A., Ruppert, T., Bántay, L., Löcklin, A., Jakab, L., Abonyi, J.: Real-time locating system in production management. Sensors 20(23), 1–22 (2020). https://doi.org/10.3390/s20236766
Ramadan, M., Salah, B., Othman, M., Arsath, A.A.: Industry 4.0-based real-time scheduling and dispatching in lean manufacturing systems. Sustainability 12(6), 2272 (2020). https://doi.org/10.3390/su12062272
Rega, A., et al.: Collaborative workplace design: a knowledge-based approach to promote human–robot collaboration and multi-objective layout optimization. Appl. Sci. 11(24), 12147 (2021). https://doi.org/10.3390/app112412147
Reisinger, J., Hollinsky, P., Kovacic, I.: Design guideline for flexible industrial buildings integrating industry 4.0 parameters. Sustainability 13(19), 10627 (2021). https://doi.org/10.3390/su131910627
Santos, J.A.M., Sousa, J.M.C., Vieira, S.M., Ferreira, A.F.: Many-objective optimization of a three-echelon supply chain: a case study in the pharmaceutical industry. Comput. Ind. Eng. 173, 108729 (2022). https://doi.org/10.1016/j.cie.2022.108729
Tripathi, V., et al.: An agile system to enhance productivity through a modified value stream mapping approach in industry 4.0: a novel approach. Sustainability 13(21), 11997 (2021). https://doi.org/10.3390/su132111997
Tripathi, V., et al.: A novel smart production management system for the enhancement of industrial sustainability in industry 4.0. Math. Probl. Eng. 2022(2653906823) (2022). https://doi.org/10.1155/2022/6424869
Trstenjak, M., Opetuk, T., Đukić, G., Cajner, H.: Logistics 5.0 implementation model based on decision support systems. Sustainability 14(11), 6514 (2022). https://doi.org/10.3390/su14116514
Zhang, Q., Chen, Y., Lin, W., Chen, Y., Wang, T.: Optimizing medical enterprise’s operations management considering corporate social responsibility under industry 5.0. Discrete Dyn. Nat. Soc. 2021(2606655010) (2021). https://doi.org/10.1155/2021/9298166
Zhou, L., et al.: Production and operations management for intelligent manufacturing: a systematic literature review. Int. J. Prod. Res. 60(2), 808–846 (2022). https://doi.org/10.1080/00207543.2021.2017055
Acknowledgments
This research received funding from the Generalitat Valenciana: INVEST/2022/249, within the framework of the Plan de Recuperación, Transformación y Resiliencia funded by the European Union – NextGeneration and PROMETEO/2021/065; and grant PDC2022-133957-I00 (CADS4.0-II) funded by MCIN/AEI /10.13039/501100011033 and by European Union Next Generation EU/PRTR.
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Guerrero, B., Mula, J., Poler, R. (2024). Sustainable Operations Management Towards Industry 5.0. In: Bautista-Valhondo, J., Mateo-Doll, M., Lusa, A., Pastor-Moreno, R. (eds) Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023). CIO 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 206. Springer, Cham. https://doi.org/10.1007/978-3-031-57996-7_42
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