Merging capacity for a remanufacturing system is studied in this paper. In the system under study, there are two streams for returns and each stream has its dedicated processing line. Returns may originate from two channels: a) the customers, when they deem that the product has met its end-of-life conditions; b) the production line, when the conformance of the product to the specified quality standards is under question. The arrival of the returned products is random and based on a Poisson process. All of the returned products are stored in a common warehouse. Two warehousing strategies are investigated and compared in this paper. The first strategy is to divide the storage space between the two streams in the way that each type of return has its predetermined space in the storage area (divided capacity). In the second strategy, storage space is not split between the two streams and each unit of return, independent of its type, is admitted if there is vacant space (merged capacity). In both strategies, the value of remanufactured products decreases over time by a known factor called the decay rate. Mathematical models to maximize the total profit in each strategy is presented and verified by a simulation model. From a practical point of view, selecting the correct strategy is an important decision for the remanufacturers because choosing the wrong policy leads to lost profits. Numerical experiments reveal that neither of the scenarios is always preferred to the other one and the choice of the optimal strategy depends on the parameters' values and product types. For instance, increasing the remanufacturing cost of the superior product, or increasing the sale price of the inferior product make the merged storage strategy more desirable. On the contrary, increasing the remanufacturing cost of the inferior product, or increasing the sale price of the superior product make the divided storage policy more appealing.
Hamed Samarghandi earned his BSc (2006) and MSc (2008) in Industrial Engineering from Amirkabir University of Technology and Sharif University of Technology, Tehran, Iran, respectively. He received his Ph.D. from the Department of Mechanical and Manufacturing Engineering, University of Manitoba, Canada in January 2013. Hamed is an assistant professor in the Department of Finance and Management Science, Edwards School of Business since July 2013.
His research interests consist of the applications of mathematical programming in various settings including service and manufacturing sector. Hamed has published papers in top-tiered refereed journals such as EJOR, COR, EJIE, IJPR, IJAMT, CIE, IJMHEUR, etc. in areas such as scheduling optimization, facility layout planning, and healthcare optimization.
Hamed's work experience includes several years of management consultation in different settings such as automotive industry, banking and commerce, and not-for-profit healthcare environments including CancerCare Manitoba.
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