DOI: 10.5937/jaes0-31313
This is an open access article distributed under the CC BY 4.0
Volume 20 article 922 pages: 212-220
To stay competitive in turbulent business environments, manufacturing firms’ managers today constantly seek ways to reduce order response time, smooth production schedules, ensure the quality of their products, and lower overall making and shipping costs. This study incorporates an outsourcing strategy and in-house quality assurance into a production-shipment problem to address the aforementioned operational goals. The objectives are to simultaneously find the optimal fabrication batch size and frequency of delivery that minimize the system’s relevant costs and reveal in-depth information regarding the impact of diverse system parameters on the optimal policy and system cost. This study develops a model and uses the optimization method to resolve the problem. The research results facilitate managerial decisions in such a real-life situation.
The authors thank the Ministry of Science and Technology of Taiwan for its kind support to this study under contract number: MOST-104-2410-H-324-008-MY2.
1. Leavy, B. (1996). Outsourcing strategy and a learning dilemma. Production and Inventory Management Journal, 37(4), 50-54.
2. Chalos, P., Sung, J. (1998). Outsourcing decisions and managerial incentives. Decision Sciences, 29(4), 901-917. https://doi.org/10.1111/j.1540-5915.1998. tb00881.x
3. Levina, N., Ross, J.W. (2003). From the vendor's perspective: Exploring the value proposition in information technology outsourcing. MIS Quarterly: Management Information Systems, 27(3), 331-364. https://doi.org/10.2307/30036537
4. Serrato, M.A., Ryan, S.M., Gaytán, J. (2007). A Markov decision model to evaluate outsourcing in reverse logistics. International Journal of Production Research, 45(18-19), 4289-4315. https://doi.org/10.1080/00207540701450161
5. Proff, H. (2011). Where differentiating automobile manufacturers go wrong: Strategic challenges posed by increased outsourcing. International Journal of Automotive Technology and Management, 11(1), 16-35. DOI: 10.1504/IJATM.2011.038119
6. Balachandran, K.R., Wang, H-W., Li, S-H., Wang, T. (2013). In-house capability and supply chain decisions. Omega, 41(2), 473-484. https://doi.org/10.1016/j.omega.2012.01.003
7. Chiu, Y-S.P., Liang, G-M., Chiu, S.W. (2016). Solving a fabrication lot-size and shipping frequency problem with an outsourcing policy and random scrap. Mathematical and Computational Applications, 21(4), Article No. 45. https://doi.org/10.3390/mca21040045
8. Skowronski, K., Benton Jr., W.C. (2018). The influence of intellectual property rights on poaching in manufacturing outsourcing. Production and Operations Management, 27(3), 531-552. https://doi.org/10.1111/poms.12813
9. Cortinhal, M.J., Lopes, M.J., Melo, M.T. (2019). A multi-stage supply chain network design problem with in-house production and partial product outsourcing. Applied Mathematical Modelling, 70, 572-594. https://doi.org/10.1016/j.apm.2019.01.046
10. Thongrawd, C., Skulitsariyaporn, C., Sirisopana, S., Chomchom, N. (2020). The impact of the strategic supplier partnership, and strategic outsourcing on the supply chain performance: The mediating role of customer relationship. International Journal of Supply Chain Management, 9(2), 562-571. https://ojs.excelingtech.co.uk/index.php/IJSCM/article/view/4661
11. Chiu, Y-S.P., Sung, P-C., Chiu, V. (2020). A two-phase solution approach for a manufacturing-distribution problem with rework, outsourcing, and multi-shipment policy. Journal of Applied Engineering Science, 18(4), 505-509. https://doi.org/10.5937/jaes0-26156
12. Rosenblatt, M.J., Lee, H. L. (1986). Economic production cycles with imperfect production processes. IIE Transactions, 18, 48-55. https://doi.org/10.1080/07408178608975329
13. Rahim, M.A., Ben-Daya, M. (2001). Joint determination of production quantity, inspection schedule and quality control for imperfect process with deteriorating products. Journal of the Operational Research Society, 52, 1370-1378. https://doi.org/10.1057/palgrave.jors.2601238
14. Ojha, D., Sarker, B.R., Biswas, P. (2007). An optimal batch size for an imperfect production system with quality assurance and rework. International Journal of Production Research, 45(14), 3191-3214. https://doi.org/10.1080/00207540600711853
15. Sana, S.S. (2010). A production–inventory model in an imperfect production process. European Journal of Operational Research, 200(2), 451-464. https://doi.org/10.1016/j.ejor.2009.01.041
16. Adazabra, A.N., Viruthagiri, G., Shanmugam, N. (2018). Manufacture of lightweight clay bricks with improved thermal insulation properties via the incorporation of spent shea waste. Journal of Applied Research and Technology, 16(3), 186-203. https://jart.icat.unam.mx/index.php/jart/article/view/717
17. Tannady, H., Gunawan, E., Nurprihatin, F., Wilujeng, F.R. (2019). Process improvement to reduce waste in the biggest instant noodle manufacturing company in South East Asia. Journal of Applied Engineering Science, 17(2), 203-212. https://doi.org/10.5937/jaes17-18951
18. Ben Fathallah, B., Saidi, R., Dakhli, C., Belhadi, S., Yallese, M.A. (2019). Mathematical modelling and optimization of surface quality and productivity in turning process of aisi 12l14 free-cutting steel. International Journal of Industrial Engineering Computations, 10(4), 557-576. http://dx.doi.org/10.5267/j.ijiec.2019.3.001
19. Pinto, G., Silva, F.J.G., Fernandes, N.O., Casais, R., Baptista, A., Carvalho, C., (2020). Implementing a maintenance strategic plan using TPM methodology, International Journal of Industrial Engineering and Management, 11(3), 192-204. http://dx.doi.org/10.24867/IJIEM-2020-3-264
20. Taft, E.W. (1918). The most economical production lot. Iron Age, 101, 1410–1412.
21. Goyal, S.K. (1977). Integrated inventory model for a single supplier - single customer problem. International Journal of Production Research, 15(1), 107-111. https://doi.org/10.1080/00207547708943107
22. Banerjee, A. (1986). A joint economic-lot-size model for purchaser and vendor. Decision Sciences, 17(3), 292-311. https://doi.org/10.1111/j.1540-5915.1986.tb00228.x
23. Viswanathan, S. (1998). Optimal strategy for the integrated vendor-buyer inventory model. European Journal of Operational Research, 105(1), 38-42. https://doi.org/10.1016/S0377-2217(97)00032-5
24. Sarker, B.R., Diponegoro, A. (2009). Optimal production plans and shipment schedules in a supply-chain system with multiple suppliers and multiple buyers. European Journal of Operational Research, 194(3), 753-773. https://doi.org/10.1016/j.ejor.2008.01.025
25. Chiu, S.W., Chen, H.-M., Lin, H.-D., Chiu, Y.-S.P. (2018). Optimization of an intra-supply chain system with unreliable production facility. Journal of Applied Engineering Science, 16(2), 192-201. https://scindeks.ceon.rs/article.aspx?artid=1451-41171802192C
26. Buriticá, N.C., Escobar, J.W., Gutiérrez, R. (2018). Supply network design by using clustering and mixed integer programming, International Journal of Industrial Engineering and Management, 9(2), 59-68. https://www.researchgate.net/publication/327882621
27. López-Ruíz, S., Carmona-Benítez, R.B. (2019). The design of a liquefied natural gas (LNG) distribution network of a company operating in Mexico. Journal of Applied Research and Technology, 17(4), 213-249. https://jart.icat.unam.mx/index.php/jart/article/view/818
28. Bouziyane, B., Dkhissi, B., Cherkaoui, M. (2020). Multiobjective optimization in delivering pharmaceutical products with disrupted vehicle routing problem. International Journal of Industrial Engineering Computations, 11(2), 299-316. http://dx.doi.org/10.5267/j.ijiec.2019.7.003
29. Shavdinova, M., Aronson, K., Borissova, N. (2020). Development of condenser mathematical model for research and development of ways to improve its efficiency. Journal of Applied Engineering Science, 18(4), 578-585. https://aseestant.ceon.rs/index.php/jaes/article/view/27517
30. Rardin, R.L. (1998). Optimization in Operations Research. Prentice-Hall, New Jersey, 739-741.