Investigation into skill leveled operators in a multi-period cellular manufacturing system with the existence of multi-functional machines

Document Type : Article

Authors

Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran

Abstract

Many works published in the area of cellular manufacturing system are based on the assumption that machines are reliable in the whole production horizon without any break down. As such assumptions often are not realistic, to contribute to closing this gap to reality, the model has been modified by additionally including  machine reliability, alternative process routings and workforce assignment in a dynamic environment. In this research to integrate this aspects, the modified problem has been defined and formulated and an extended mixed integer multi-period mathematical model has been proposed.
In order to evaluate the effectiveness and capability of the extended model, some hypothetical numerical instances are generated and computational experiment are carried out using Gams optimization package. Experimental results demonstrate that the demand value can affect the machine breakdown rate, and a machine with a minimum breakdown rate is implemented more often than others. Moreover, the observed trade-off between the workforce-related costs and the cell-formation costs indicates that workforce-related issues have a significant impact on the total efficiency of the system. The proposed model can be implemented in medium- and large-scale manufacturing companies.

Keywords

References

  1. References:

    1. Liu, C., Wang, J., and Leung, J.Y.T. Integrated bacteria foraging algorithm for cellular manufacturing in supply chain considering facility transfer and production planning", Applied Soft Computing, 62, pp. 602{618 (2018).
    2. Askin, R.G. Contributions to the design and analysis of cellular manufacturing systems", International Journal of Production Research, 51, pp. 6778{6787 (2013).
    3. Ameli, M.S.J. and Arkat, J. Cell formation with alternative process routings and machine reliability consideration", The International Journal of Advanced Manufacturing Technology, 35, pp. 761{768 (2008).
    4. Bulgak, A.A. and Bektas T. Integrated cellular manufacturing systems design with production planning and 3232 M. Rafiee and A. Mohamaditalab/Scientia Iranica, Transactions E: Industrial Engineering 27 (2020) 3219{3232 dynamic system recon_guration", European Journal of Operational Research, 192, pp. 414{428 (2009).
    5. Mehdizadeh, E., Niaki S.V.D., and Rahimi, V. A vibration damping optimization algorithm for solving a new multi-objective dynamic cell formation problem with workers training", Computers & Industrial Engineering, 101, pp. 35{52 (2016).
    6. Mahdavi, I., Aalaei, A., Paydar, M.M., and Solimanpur, M. Designing a mathematical model for dynamic cellular manufacturing systems considering production planning and worker assignment", Computers & Mathematics with Applications, 60, pp. 1014{1025 (2010). 7. Aryanezhad, M.B., Deljoo, V., and Mirzapour Al-e- Hashem, S. Dynamic cell formation and the worker assignment problem: a new model", The International Journal of Advanced Manufacturing Technology, 41, pp. 329{342 (2009). 8. Bagheri, M. and Bashiri M. A new mathematical model towards the integration of cell formation with workforce assignment and inter-cell layout problems in a dynamic environment", Applied Mathematical Modelling, 38, pp. 1237{1254 (2014). 9. Javadi, B., Jolai, F., Slomp, J., Rabbani, M., and Tavakkoli- Moghaddam, R. An integrated approach for the cell formation and layout design in cellular manufacturing systems", International Journal of Production Research, 51, pp. 6017{6044 (2013). 10. Bagheri, M., Sadeghi, S., and Saidi-Mehrabad, M. A benders' decomposition approach for dynamic cellular manufacturing system in the presence of unreliable machines", Journal of Optimization in Industrial Engineering, 17, pp. 37{49 (2015). 11. Bayram, H. and S_ahin, R. A comprehensive mathematical model for dynamic cellular manufacturing system design and linear programming embedded hybrid solution techniques", Computers & Industrial Engineering, 91, pp. 10{29 (2016). 12. Azadeh, A., Ravanbakhsh, M., Rezaei-Malek, M., Sheikhalishahi, M., and Taheri-Moghaddam, A. Unique NSGA-II and MOPSO algorithms for improved dynamic cellular manufacturing systems considering human factors", Applied Mathematical Modelling, 48, pp. 655{672 (2017). 13. Liu, C., Wang, J., and Leung, J.Y.T. Worker assignment and production planning with learning and forgetting in manufacturing cells by hybrid bacteria foraging algorithm", Computers & Industrial Engineering, 96, pp. 162{179 (2016). 14. Mehdizadeh, E. and Rahimi, V. An integrated mathematical model for solving dynamic cell formation problem considering workforce assignment and inter/intra cell layouts", Applied Soft Computing, 42, pp. 325{341 (2016). 15. Ra_ei, H. and Ghodsi, R. A bi-objective mathematical model toward dynamic cell formation considering labor utilization", Applied Mathematical Modelling, 37, pp. 2308{2316 (2013). 16. Sakhaii, M., Tavakkoli-Moghaddam, R., Bagheri, M., and Vatani, B. A robust optimization approach for an integrated dynamic cellular manufacturing system and production planning with unreliable machines", Applied Mathematical Modelling, 40, pp. 169{191 (2016). 17. Nouri, H. Development of a comprehensive model and BFO algorithm for a dynamic cellular manufacturing system", Applied Mathematical Modelling, 40, pp. 1514{1531 (2016).
Scientia Iranica
Volume 27, Issue 6 - Serial Number 6
Transactions on Industrial Engineering (E)
November and December 2020
Pages 3219-3232

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History

  • Receive Date: 03 June 2017
  • Revise Date: 03 July 2018
  • Accept Date: 21 July 2019

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