Integration of lot sizing and scheduling models to minimize production cost and time in the automotive industry
DOI:
https://doi.org/10.12928/ijio.v1i1.2753Keywords:
Lot planning, Scheduling, Genetic Algorithm, Taguchi, Production CostAbstract
Lot planning and production scheduling are important processes in the manufacturing industry. This study is based on the case study of automotive spare parts manufacturing firm (Firm-A), which produces various products based on customer demand. Several complex problems have been identified due to different production process flows for different products with different machine capability considerations at each stage of the production process. Based on these problems, this study proposes three integrated models that include lot planning and scheduling to minimize production costs, production times, and production costs and time simultaneously. These can be achieved by optimizing model solutions such as job order decisions and production quantities on the production process. Next, the genetic algorithm (GA) and the Taguchi approach are used to optimize the models by finding the optimal model solution for each objective. Model testing is presented using numerical examples and actual case data from Firm-A. The model testing analysis is performed using Microsoft Excel software to develop a model based on mathematical programming to formulate all three objective functions. Meanwhile, GeneHunter software is used to represent the optimization process using GA. The results show production quantity and job sequence play an essential role in reducing the cost and time of production by Rp 42.717.200,00 and 31392.82 minutes (65.4 days), respectively. The findings of the study contribute to the production management of Firm-A in helping to make decisions to reduce the time and costs of production strategically, where it provides a guideline for complex production activities.References
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Rohaninejad, M., Kheirkhah, A., & Fattahi, P. (2015). Simultaneous lot-sizing and scheduling in flexible job shop problems. International Journal of Advanced Manufacturing Technology, 78(1–4), 1–18. https://doi.org/10.1007/s00170-014-6598-5
Zhao, H., Huang, E., Dou, R., & Wu, K. (2019). A multi-objective production planning problem with the consideration of time and cost in clinical trials. Expert Systems with Applications, 124, 25–38. https://doi.org/10.1016/j.eswa.2019.01.038
Almeder, C., Klabjan, D., Traxler, R., & Almada-lobo, B. (2014). Lead time considerations for the multi-level capacitated lot-sizing problem. European Journal of Operational Research, 241, 1–12. https://doi.org/10.1016/j.ejor.2014.09.030
Chong, K. E., & Asih, H. M. (2015). An Integrated Robust Optimization Model of Capacity Planning under Demand Uncertainty in Electronic Industry. International Journal of Mechanical & Mechatronics Engineering, 15(03), 88–96.
Clark, A., Mahdieh, M., & Rangel, S. (2014). Production lot sizing and scheduling with non-triangular sequence-dependent setup times. International Journal of Production Research, 52(8), 2490–2503. https://doi.org/10.1080/00207543.2014.885662
Han, J. H., Lee, J. Y., & Kim, Y. D. (2019). Production planning in a two-level supply chain for production-time-dependent products with dynamic demands. Computers and Industrial Engineering, 135(May), 1–9. https://doi.org/10.1016/j.cie.2019.05.036
Hu, Y., Guan, Y., Han, J., & Wen, J. (2017). Joint Optimization of Production Planning and Capacity Adjustment for Assembly System. Procedia CIRP, 62, 193–198. https://doi.org/10.1016/j.procir.2016.06.029
Leuveano, R. A. C., Bin Jafar, F. A., Saleh, C., & Bin Muhamad, M. R. (2014). Incorporating Transportation Cost into Joint Economic Lot Size For Single Vendor-Buyer. Journal of Software, 9(5), 1313–1323. https://doi.org/10.4304/jsw.9.5.1313-1323
Liu, M., Wang, S., & Chu, C. (2013). Scheduling deteriorating jobs with past-sequence-dependent delivery times. International Journal of Production Economics, 144(2), 418–421. https://doi.org/10.1016/j.ijpe.2013.03.009
Pinedo, M. L. (2012). Scheduling: theory, algorithms, and systems. Springer Science & Business Media.
Quadt, D., & Kuhn, H. (2007). Batch scheduling of jobs with identical process times on flexible flow lines. International Journal of Production Economics, 105(2), 385–401. https://doi.org/10.1016/j.ijpe.2004.04.013
Rahman, M. N. A., Leuveano, R. A. C., Bin Jafar, F. A., Saleh, C., & Deros, B. M. (2015). Total cost reduction using a genetic algorithm for multi-vendor and single manufacturer. International Journal of Mathematical Models and Methods in Applied Sciences, 9, 566–575.
Rahman, M. N. A., Zubir, N. S. M., Leuveano, R. A. C., Ghani, J. A., & Wan Mahmood, W. M. F. (2014). Reliability study of solder paste alloy for the improvement of solder joint at surface mount fine-pitch components. Materials, 7(12), 7706–7721. https://doi.org/10.3390/ma7127706
Ramezanian, R., & Saidi-mehrabad, M. (2013). A mathematical model for integrating lot-sizing and scheduling problem in capacitated flow shop environments. The International Journal of Advanced Manufacturing Technology, 66(1–4), 347–361. https://doi.org/10.1007/s00170-012-4329-3
Rohaninejad, M., Kheirkhah, A., & Fattahi, P. (2015). Simultaneous lot-sizing and scheduling in flexible job shop problems. International Journal of Advanced Manufacturing Technology, 78(1–4), 1–18. https://doi.org/10.1007/s00170-014-6598-5
Zhao, H., Huang, E., Dou, R., & Wu, K. (2019). A multi-objective production planning problem with the consideration of time and cost in clinical trials. Expert Systems with Applications, 124, 25–38. https://doi.org/10.1016/j.eswa.2019.01.038
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Published
2020-02-28
How to Cite
Badri, H. M., Khamis, N. K., & Ghazali, M. J. (2020). Integration of lot sizing and scheduling models to minimize production cost and time in the automotive industry. International Journal of Industrial Optimization, 1(1), 1–14. https://doi.org/10.12928/ijio.v1i1.2753
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