In remanufacturing research, most researchers predominantly emphasised on the recovery of whole product (core) rather than at the component level due to its complexity. In contrast, this paper addresses the challenges to focus on remanufacturing through component recovery, so as to solve production planning problems of hybrid remanufacturing and manufacturing systems. To deal with the uncertainties of quality and quantity of product returns, the processing time of remanufacturing, remanufacturing costs, as well as market demands, a robust optimisation model was developed in this research and a case study was used to evaluate its effectiveness and efficiency. To strengthen this research, a sensitivity analysis of the uncertain parameters and the original equipment manufacturer’s (OEM’s) pricing strategy was also conducted. The research finding shows that the market demand volatility leads to a significant increase in the under fulfilment and a reduction in OEM’s profit. On the other hand, recovery cost reduction, as endogenous cost saving, encourages the OEM to produce more remanufactured products with the increase in market demand. Furthermore, the OEM may risk profit loss if they raise the price of new products, and inversely, they could gain more if the price of remanufactured products is raised.
Bibliographical noteThis is an Accepted Manuscript of an article published by Taylor & Francis in Han, S, Ma, W, Zhao, L, Zhang, X, Lim, MK, Yang, S & Leung, S 2016, 'A robust optimisation model for hybrid remanufacturing and manufacturing systems under uncertain return quality and market demand' International Journal of Production Research, vol 54, no. 17, pp. 5056-5072 on 15th February 2016, available online: http://www.tandfonline.com/10.1080/00207543.2016.1145815
- production planning
- robust optimisation model
Han, S., Ma, W., Zhao, L., Zhang, X., Lim, M. K., Yang, S., & Leung, S. (2016). A robust optimisation model for hybrid remanufacturing and manufacturing systems under uncertain return quality and market demand. International Journal of Production Research, 54(17), 5056-5072. https://doi.org/10.1080/00207543.2016.1145815