Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

An Operation Planning Model in a Reconfigurable Manufacturing System with Sustainability

Document Type : Original Article

Authors
Department of Industrial Engineering, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran
Abstract
There are different forms and modes of the planning problem in complex reconfigurable manufacturing systems (RMS), most of which have primarily focused on the effective and efficient utilization of tools and machine allocation. However, sustainability considerations have often been overlooked in such approaches. This study is designed to introduce a planning model for the operation stages of machining complex products within a factory equipped with a reconfigurable manufacturing system. The primary objective of the proposed model is to enhance system performance while ensuring optimal, low-cost utilization of equipment, machinery, and tools. Unlike traditional planning approaches, this model extends beyond mere production efficiency by integrating sustainability-oriented strategies. Specifically, it incorporates key elements such as reducing energy consumption, minimizing idle time, optimizing operation durations, and improving the processes of tool exchange and replacement. By addressing both operational effectiveness and environmental responsibility, the model provides a holistic framework for planning in RMS environments. Ultimately, the integration of sustainability concepts into reconfigurable manufacturing planning not only contributes to lowering production costs but also strengthens long-term competitiveness and resilience in manufacturing industries, aligning industrial practices with contemporary goals of sustainable development.
Keywords

  • Mehrabi, M. G., Ulsoy, A. G., Koran, Y., & Heytler, P. (2002). Trends and perspectives in flexible and reconfigurable manufacturing systems. Journal of Intelligent Manufacturing, 13(2), 135–146. https://doi.org/10.1023/A:1014536330551
  • Mehrabi, M. G., Ulsoy, A. G., & Koran, Y. (2000). Reconfigurable manufacturing systems: Key to future manufacturing. Journal of Intelligent Manufacturing, 11, 403–419. https://doi.org/10.1023/A:1008930403506
  • Koren, Y. (2006). General RMS characteristics. Comparison with dedicated and flexible systems. In A. I. Dashchenko (Ed.), Reconfigurable manufacturing systems and transformable factories (Netherlands: Springer-Verlag).
  • Azab, A., & Naderi, B. (2015). Modelling the problem of production scheduling for reconfigurable manufacturing systems. Procedia CIRP, 33, 76–80. https://doi.org/10.1016/j.procir.2015.06.015
  • Caradonna, J. L. (2014). Sustainability today: 2000–present. In Sustainability. https://doi.org/10.1093/oso/9780199372409.003.0010
  • Kates, R. W. (2010). Readings in sustainability science and technology: An introduction to the key literatures of sustainability science (CID Working Paper No. 213).
  • Adams, W. M. (2006). The future of sustainability: Re-thinking environment and development in the twenty-first century. In Report of the IUCN Renowned Thinkers Meeting (pp. 2009–2011).
  • Son, H., Choi, H.-J., & Park, H. W. (2010). Design and dynamic analysis of an arch-type desktop reconfigurable machine. International Journal of Machine Tools & Manufacture, 50(6), 575–584. https://doi.org/10.1016/j.ijmachtools.2010.02.006
  • Tang, L., Yip-Hoi, D. M., & Wang, W. (2004). Concurrent line-balancing, equipment selection and throughput analysis for multi-part optimal line design. International Journal of Manufacturing Science and Production, 6, 71–81. https://doi.org/10.1515/IJMSP.2004.6.1-2.71
  • Meng, X. (2010). Modeling of reconfigurable manufacturing systems based on colored timed object-oriented Petri nets. Journal of Manufacturing Systems, 29(2–3), 81–90. https://doi.org/10.1016/j.jmsy.2010.11.002
  • Abbasi, M., & Houshmand, M. (2011). Production planning and performance optimization of reconfigurable manufacturing systems using genetic algorithm. International Journal of Advanced Manufacturing Technology, 54, 373–392. https://doi.org/10.1007/s00170-010-2914-x
  • Lou, H. (2006). Reconfiguration policy of reconfigurable manufacturing systems based on graph theory. Jixie Gongcheng Xuebao (Chinese Journal of Mechanical Engineering, 42(03), 22. https://doi.org/10.3901/JME.2006.03.022
  • Shabaka, A. I., & Elmaraghy, H. A. (2007). Generation of machine configurations based on product features. International Journal of Computer Integrated Manufacturing, 20(4), 355–369. https://doi.org/10.1080/09511920600740627
  • Azab, A., & Gomaa, A. H. (2011). Optimal sequencing of machining operations for changeable manufacturing. In 4th International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV2011). Montreal, Canada. https://doi.org/10.1007/978-3-642-23860-4_19
  • Bensmaine, A., Dahane, M., & Benyoucef, L. (2013). A non-dominated sorting genetic algorithm based approach for optimal machines selection in reconfigurable manufacturing environment. Computers & Industrial Engineering, 66(3), 519–524. https://doi.org/10.1016/j.cie.2012.09.008
  • Musharavati, F., & Hamouda, A. S. M. (2012). Enhanced simulated-annealing-based algorithms and their applications to process planning in reconfigurable manufacturing systems. Advances in Engineering Software, 45, 80–90. https://doi.org/10.1016/j.advengsoft.2011.09.017
  • Sujova, A., Marcinekova, K., & Hittmar, S. (2017). Sustainable optimization of manufacturing process effectiveness in furniture production. Sustainability, 9(6), 923. https://doi.org/10.3390/su9060923
  • Xiaowen, X., Beirong, Z., & Wei, X. (2013). Configuration optimization method of reconfigurable manufacturing systems. Research Journal of Applied Sciences, Engineering and Technology, 6(8), 1389–1393. https://doi.org/10.19026/rjaset.6.3961
  • Das, K., Baki, M. F., & Li, X. (2009). Optimization of operation and changeover time for production planning and scheduling in a flexible manufacturing system. Computers & Industrial Engineering, 56(1), 283–293. https://doi.org/10.1016/j.cie.2008.06.001
  • Bhargav, A., Venkatachalapathi, N., & Kumar, D. (2016). Machine tool scheduling problem for reconfigurable manufacturing system (RMS). Australian Journal of Basic and Applied Sciences, 10(18), 176–180.
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Volume 4, Issue 1
Winter 2022
Pages 39-47

  • Receive Date 03 February 2022
  • Revise Date 04 March 2022
  • Accept Date 28 March 2022