Strategic network design for reverse logistics and remanufacturing using new and old product modules
Introduction
Implementation of legislation, social responsibility, corporate imaging, environmental concern, economic benefits and customer awareness are forcing OEMs not only to provide more environmentally friendly products but also to take back used products at its end of life. Products can also be returned for reasons such as customer dissatisfaction and warranty (Rogers and Tibben-Lembke, 1999, Tibben-Lembke, 2002). Such products can be sorted for reuse, remanufacture, recycle and disposal. Reuse of used products by some value addition is not a new concept. Also, industries are using remanufacturing for expensive products such as turbines used in airplane and electricity generation systems. In these cases recovery of used products is economically more attractive than disposal (Koh, Hwang, Sohn, & Ko, 2002). OEMs are incorporating ‘extended producer responsibility’ (EPR) to reduce wastes in a used product (Carter & Ellram, 1998). While on the other hand, they are implementing networks to take back their products through various channels. However, if returned products are not handled efficiently then OEMs would incur larger costs that can increase the cost of the new product. Therefore, network for return of products should be efficient and cost effective.
On the design part, OEMs are increasingly modularizing their products (Fredrikson, 2006) not only to reduce the steps for final assembly but also to facilitate faster dismantling and repair of used products (Ulrich & Tung, 1991). Therefore, modularization helps to avoid disposal of usable modules retrieved from the used products (Dowlatshahi, 2000). Also, OEMs are substituting certain parts and materials by recyclable and environment friendly alternatives (Gupta & Isaacs, 1997).
In this paper, a mathematical model is proposed for the design of a RL network handling product returns. The model considers the supply of returned products through third party collectors. It considers storing, reprocessing, remanufacturing facilities and new module suppliers in the network. If the recovered modules are not sufficient to remanufacture the products to meet the demand, then certain quantities of certain new modules need to be purchased. We also consider demand for used modules in the secondary markets. The design of such a network is strategic as it involves a decision on the number, location and capacities of various facilities and allocation of material flows between them (Dethloff, 2001, Dowlatshahi, 2005, Jayaraman et al., 1999, Lu and Bostel, 2007, Realff et al., 2000) and is one of the most challenging elements of managing RL operations (Pochampally & Gupta, 2005). A properly designed network can also enhance dealing with remanufacturing activities (Prahinski & Kocabasoglu, 2006) and competitive advantage (Gungor & Gupta, 1999).
Section snippets
Research on design of RL network
Several researchers have studied the design of RL network focusing on their cost effectiveness. Studies have concluded that for recycling of the returned products, logistics costs account for a large share of the total costs (Beullens, 2004, Jahre, 1995, Stock, 1992). RL requires high investment and a high portion of logistics costs (Nagel & Meyer, 1999). The RL cost can vary from 4% (Rogers, 2001) to 9.49% (Daugherty, Autry, & Ellinger, 2001) of the total logistics cost. In the retail and
Model formulation
A generic network diagram used for the analysis is given in Fig. 1. It involves nine echelons. As suggested by Biehl et al. (2007), the model assumes retailers as collecting points a well. The other echelons considered in the model are warehouses (for storage and consolidation), reprocessing centres for inspection and dismantling, remanufacturing factories, recycling centres, disposal sites and markets for spare parts and remanufactured products. The network considers pre-selected new module
Model implementation
A nine echelon network consisting of five retailers, four warehouses, three RPC’s, five spare markets, three factories, one recycling centre, one disposal site, six new module suppliers and six distribution centres has been considered for the model implementation. Consistent to earlier studies (Mabini et al., 1992, Mitra, 2007, Mostard and Teunter, 2006, Salema et al., 2006), a certain percentage (30% in this case) of returned modules of the returned products are assumed to be disposed. Good
Conclusions
This paper proposes a model to for designing reverse logistics networks. An idea presented in this paper is allowing only a portion of capacity in warehouses, RPC’s and factories for RL. This can also simulate current pattern used by some of the industry to use existing warehouses, dismantling centres and factory lines for returned products. Due to the difficulty in establishing whole new entities to cater to the needs for RL, some companies segregate their capacities to handle new products and
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