Near optimal buffer allocation in remanufacturing systems with N-policy H. Kıvanç Aksoy a,1 , Surendra M. Gupta b, * a Department of Statistics, Eskis ßehir Osmangazi University, Eskis ßehir 26480, Turkey b Laboratory for Responsible Manufacturing 334 SN, Department of Mechanical and Industrial Engineering, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA article info Article history: Received 1 February 2010 Received in revised form 12 May 2010 Accepted 9 June 2010 Available online 12 June 2010 Keywords: Buffer allocation N-policy Performance evaluation Queueing networks Remanufacturing Throughput abstract We introduce a near optimal buffer allocation plan (NOBAP) specifically developed for a cellular reman- ufacturing system with finite buffers where the servers follow N-policy. The term N-policy is used for the situation where the server leaves primary work to tend to an external workload assigned to him (such as processing additional tasks or performing preventive maintenance of equipments) every time the server becomes idle and does not return back to his primary work until the queue size in front of the primary work reaches a threshold value of N (P1). The remanufacturing system considered here consists of three modules, viz., the disassembly module for returned products, the testing module and the remanufactur- ing module. In order to analyze the system we propose an algorithm that uses an open queueing network, decomposition principle and expansion methodology. The buffer allocation algorithm distributes a given number of available buffer slots among the remanufacturing system stations to optimize the system’s performance. The algorithm has been rigorously tested using a variety of experimental conditions. From the results, it is clear that the algorithm’s performance is robust, consistent and produces excellent results. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Remanufacturing is an industrial process in which worn-out products are restored to ‘‘like-new” conditions. Thus, remanufac- turing provides quality standards of new products with used parts. Remanufacturing is not only a direct and preferable way to reduce the amount of waste generated, it also reduces the consumption of new materials and energy resources. Recycling, on the other hand, is a process performed to retrieve the material content of used and non-functioning products without retaining the identity of the ori- ginal product. Remanufacturing of durable goods has become an important alternative to assembling new products. This is a direct consequence of the implementation of extended manufacturer responsibility, together with the new more rigid legislation and public awareness of the environment. In addition, the economic attractiveness of remanufacturing products, instead of disposing them, has further fueled this phenomenon. Remanufacturing is an important element of product recovery. Product recovery management is concerned with the collection of used and discarded products and the exploration of the opportuni- ties to remanufacture the products, reuse the components or recycle the materials. The objective of product recovery manage- ment, as stated by Thierry, Salomon, van Nunen, and van Wassenh- ove (1995), is ‘‘to recover as much of the economic (and ecological) value as reasonably possible, thereby reducing the ultimate quanti- ties of waste”. Remanufacturing is one of the most desirable options of product recovery. Remanufacturing operations tend to be labor intensive that lead to significant variability in the processing times at various shop floor operations. The uncertainties surrounding the returned products further complicate the modeling and analysis of product recovery problems. As such, forecasting the quantity and the quality levels of used products are difficult. There are two differ- ent types of uncertainties that affect the remanufacturing process: internal uncertainty and external uncertainty. Internal uncertainty comprises of the variations within the remanufacturing process such as the quality level of the product, the remanufacturing lead time, the yield rate of the process and the possibility of system fail- ure. External uncertainty comprises of the variations originating from factors outside the remanufacturing process which include the timing, quantity and quality (re-usable rate) of the returned products, the timing and the level of demand, and the procurement lead times of new parts/products. The results of the stated uncer- tainties include undersupply or obsolescence of inventory, impro- per remanufacturing plan and loss of competitive edge in the market. See Fig. 1 for a schematic diagram of typical remanufactur- ing operations and their flows. The need to optimize a remanufacturing system’s performance is most desirable because of the aforementioned uncertainties and complexities. One can always reduce the effect of uncertainties on 0360-8352/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.cie.2010.06.004 * Corresponding author. Tel.: +1 617 373 4846; fax: +1 617 373 2921. E-mail addresses: hkaksoy@ogu.edu.tr (H. Kıvanç Aksoy), gupta@neu.edu (S.M. Gupta). 1 Tel.: +90 222 239 3750x2116; fax: +90 222 239 3578. Computers & Industrial Engineering 59 (2010) 496–508 Contents lists available at ScienceDirect Computers & Industrial Engineering journal homepage: www.elsevier.com/locate/caie