Multi-Stage Multi-Period Production Planning in Wire and Cable Industry

Authors: Mahnaz Hosseinzadeh, Shaghayegh Rezaee Amiri

Abstract:

This paper presents a methodology for serial production planning problem in wire and cable manufacturing process that addresses the problem of input-output imbalance in different consecutive stations, hoping to minimize the halt of machines in each stage. To this end, a linear Goal Programming (GP) model is developed, in which four main categories of constraints as per the number of runs per machine, machines’ sequences, acceptable inventories of machines at the end of each period, and the necessity of fulfillment of the customers’ orders are considered. The model is formulated based upon on the real data obtained from IKO TAK Company, an important supplier of wire and cable for oil and gas and automotive industries in Iran. By solving the model in GAMS software the optimal number of runs, end-of-period inventories, and the possible minimum idle time for each machine are calculated. The application of the numerical results in the target company has shown the efficiency of the proposed model and the solution in decreasing the lead time of the end product delivery to the customers by 20%. Accordingly, the developed model could be easily applied in wire and cable companies for the aim of optimal production planning to reduce the halt of machines in manufacturing stages.

Keywords: Serial manufacturing process, production planning, wire and cable industry, goal programming approach.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1317438

References:

[1] Tehran Bourse News Agency, http://www.boursenews.ir/fa/news/156728/investigating wire and cable industry in the world and Iran, -20 April 2018.
[2] E. Mehdizadeha, S.T. Akhavan Niaki, M. Hemati, “A bi-objective aggregate production planning problem with learning effect and machine deterioration: Modeling and solution”, Computers and Operations Research, vol. 91, pp. 21–36, 2018.
[3] M. Gupta, B. K. Mohanty, “Multi-stage multi-objective production planning using linguistic and numeric data-a fuzzy integer programming model”, Computers & Industrial Engineering, vol. 87, pp. 454–464, 2015.
[4] S. Beraa, I. Mukherjee, “A multistage and multiple response optimization approach for serial manufacturing system”, European Journal of Operational Research, vol. 248, pp. 44–452, 2016.
[5] S. Lu, H. Su, Y. Wang, L. Xie, Q. Zhang, Multi-product Multi-stage Production Planning with Lead Time on a Rolling Horizon Basis, IFAC-PapersOnLine. Vol. 48, pp. 1162–1167, 2015.
[6] S. Torkaman, S. M. T Fatemi Ghomi, B. Karimi, Multi-stage multi-product multi-period production planning with sequence dependent setups in closed-loop supply chain, Computers & Industrial Engineering. Vol. 113, pp. 602–613, 2017.
[7] S. Torkaman, S. M. T. Fatemi Ghomi, B. Karimi, “Hybrid simulated annealing and genetic approach for solving a multi-stage production planning with sequence-dependent setups in a closed-loop supply chain”, Applied Soft Computing, https://doi.org/10.1016/j.asoc.2017.10.019, 2017.