دانلود مقاله ISI انگلیسی شماره 1422
عنوان فارسی مقاله

طراحی شبکه لجستیک معکوس برای جمع آوری، بازیابی و برنامه ریزی مطلوب آمیخته محصول مبتنی بر کیفیت

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
1422 2012 13 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : International Journal of Production Economics, Volume 135, Issue 1, January 2012, Pages 209–221

کلمات کلیدی
زنجیره تامین حلقه بسته - طراحی محصول ماژولار - سطح کیفیت محصولات - بازیابی ماژول - مجموعه ای از محصولات بازگشتی - مدل
پیش نمایش مقاله
پیش نمایش مقاله طراحی شبکه لجستیک معکوس برای جمع آوری، بازیابی و برنامه ریزی مطلوب آمیخته محصول مبتنی بر کیفیت

چکیده انگلیسی

This study proposes an integrated, reverse logistics supply chain planning process with modular product design that produces and markets products at different quality levels. A mixed integer programming (MIP) model formulates the overall planning process required to maximize profit by considering the collection of returned products, the recovery of modules and the proportion of the product mix at different quality levels. This paper proposes the collection of returnables (end-of life, defective, product under warranty) through retail outlets combined with the recovery of modules from the collected products using a network of recovery service providers. The proposed modular product design approach would create a design criterion that provides an improved recovery process at a lower cost. This study uses a total supply chain view that considers the production, transportation and distribution of products to customers, while a numerical problem illustrates the applicability of the models.

مقدمه انگلیسی

Most of the companies currently involved in manufacturing and marketing of products have been incorporating reverse logistics (RL) in their supply chain (SC) planning as a way of complying with environmental regulations and sustainability expectations, as well as gaining a business advantage from the recovered products. The integration of RL has received significant attention from recent studies; please see the review studies, Ilgin and Gupta (2010), Subramonium et al. (2009) and Pokharel and Mutha (2009). The ability to plan for the collection of returned products, the component/product recovery process, the proportion of products to be manufactured at different quality levels and product design for recovery remains a significant challenge for SC managers; despite the fact that several companies have pursued RL, and some state-of-the-art RL research models have been published. In RL, returned products can include the following: after use (end of life or before end of life); returned under warranty; defective; obsolete products returned by the retailer (obsolescence due to emergence of new model or new technology) and products returned by consumers under exchange programs. This research does not address products that have been returned under an exchange program. The literature addresses the collection of returned products in three ways: third party logistics (Cruz-Rivera and Ertel, 2009, de Figueiredo and Mayerle, 2008, Krikke et al., 2008 and Webster and Mitra, 2007), the opening of collection centers by the remanufacturer/manufacturer (Aras and Aksen, 2008 and Tagaras and Zikopoulos, 2008) and the use of retailers (Savaskan et al., 2004 and Wojanowski et al., 2007). The collection of end-of life, returned or defective items should be driven by reasonable profit if third party logistics is to be involved. Most of the returned products do not have any value in terms of functionality (Schultmann et al., 2006), but they do offer materials that can be reprocessed. For short life cycle products like copiers, computers and cell phones, several components can be recovered to obtain functional values if the condition of the product permits. Conditions, however, are often unknown—and the same can be said for the mix of returned items. It is also crucial to address the fact that consumers do not typically have any motivation to return products (Guide et al., 2003). As such, logical planning should set collection options that provide consumers with the motivation to return products without any extra hassle like finding a collection center. Based on these two vital collection-related factors, successful development would involve retailers and selling outlets in the collection of returnables through appropriate promotional steps that would include reasonable incentives for motivating consumers (Guide, 2000). The consumer should know from the moment of purchase that the product may be returned at any outlet or retail centers with a call to company representatives or carrying the product to the retail centers. Using retail outlets in this way will provide a collaborative network of collection centers when more than one company chooses to use the same retail outlets. Retailers and selling outlets usually market several products from several suppliers/businesses. The proposed collaborative approach would make the collection of returnables a viable business component for retailers. Savaskan et al. (2004) compared third-party (3P) logistics, retail outlets and the manufacturer's own channels for collecting returnables, and concluded that collection through retailers was the best option. This paper proposes to involve retail outlets through contractual costs and benefit-based agreements with retailers for the collection of returnables. The approach would be to motivate the retailer by taking promotional steps that would ensure the collection of returnables—an approach that has the potential to develop long-term partner relations with retailers while generating a collaborative approach among several other organizations and retailers. Involving the retailer in the business of collection makes this approach practical and may be considered more viable than Wojanowski et al.'s (2007), which considered the collection of returnables using retailers under a deposit refund scheme. This study has taken into account the conclusions of Savaskan et al. (2004), which suggest considering retail outlets as collection centers. To be successful, a RL system must have product recovery and collection of returnable equally effective. The recovery process can be handled by the original manufacturer of the product, or 3P logistics, but since it is very difficult to pre-determine the quantity and quality of returned products it may not be feasible for a manufacturer to open a recovery facility for their returned or reverse-channeled products. Economic factors suggest that the most suitable recovery option would be a 3P recovery service provider (RSP) or a network of RSPs. It may be noted at this point that product recovery in a RL situation is both complex and time consuming. Recovery processes for different product types (Thiery et al., 1995) would involve different levels of expertise. The literature mentions modularity in RL as a way to avoid the futility of returned built-to-order type products (Mukhopadhyay and Setoputro, 2005) and sometimes to cope with the take back law (Fernandes and Kekale, 2005). Modular product design is an established approach for accelerating product development and creating a range of variation in product design. Some of the additional benefits of modular design have been studied by Mikkola and Gassmann (2003). This paper considers using modular product design to create the original product and obtain a reduced recovery cost by decreasing lead time and making the overall recovery process easier. Since product design is a strategic decision issue, SC planning should integrate product design in the strategic planning process to acquire its advantage in production processes (Blackhurst et al., 2005). As discussed, modular design improves production lead time and recovery process of the returned products. Inclusion of modularity while integrating product design at the strategic decision process will further enhance the RL process and overall SC performances. There is no research that considers modularity as product architecture for quick recovery the way this research does. Since the quantity of the returned products, as well as the value addition in the recovery process are not certain, this research assigns RSPs for product recovery using a contractual agreement. To obtain RL-related business advantages or even comply with the regulatory requirements, SCs should note that RL is a complex business process (Krumwiede and Sheu, 2002), and the recovered products would always be in a competing situation with new products (Horvath et al., 2005). An RL-based SC may categorize products at three quality levels (QLs): QL1 could be products that use all new components/modules; QL2 could be products that use a mixture of new and recovered components/modules and QL 3 could be products that use only recovered components/ modules. This business provision would allow SCs to use an “if-what" analysis to decide the proportion of each QL produced as a way to optimize their profit. There is a significant gap in the literature regarding how to solve the challenges faced by SC managers who wish to collect returnables, recover products from returnables, decide the proportion of product quantities at different quality levels and make the recovery process faster, easier and cost effective. Motivated by this finding, this paper proposes an effective and practicable, closed-loop SC design that addresses most of the critical issues of this gap. The contributions that distinguish this paper from the existing and past research include planning a customer-friendly returnable collection process using retail outlets when collection is a business option for the retailers; providing different quality-level selection options to the market for each product; considering modular product design architecture for a quicker, easier, cost effective recovery process and integrating a network of RSPs to handle product recovery. In addition, this paper takes a total SC view when assigning components to suppliers, producing modules and products for plants, assigning returnables to RSPs for the recovery of modules and allocating DCs to customers for overall profit maximization. This paper is organized in the following way: Section 2 reviews the relevant literature; Section 3 includes the problem statement, MIP-based closed-loop SC model and model description. Section 4 illustrates an example problem to show applicability of the model and investigates model sensitivity for the change in recovered product demand, and Section 5 concludes.

نتیجه گیری انگلیسی

This research introduces a modular product design for RL planning that minimizes recovery costs in addition to improving the overall production performance of a SC that involves new and recovered products. The additional benefits of this modular product design include obtaining reduced lead times for the production of new and recovered products; reduced lead time for the recovery process; reduced skill requirements for RSPs and the possibility that customized product models could be offered at optimum cost. The model also includes a new approach to planning products/product mixes at different quality levels to facilitate SC planners in the creation of choice options for the customers (brands) that will allow businesses to offer a warranty similar to that of the new product. To balance the ecological and profit-based aspirations, this research includes incentive criteria for collecting returnables, agreement conditions for fixing the maximum collection quantity by the retailers and the use of a percentage of recovered modules in the q=2 quality level products that builds trade-off decision options for SC managers. The model sensitivity investigation provides further insights and options to the SC managers in improving their reverse logistics based SC performances. The model uses retailers to collect returned products, which is a customer-friendly approach that created the option of using the same place for buying and returning. The proposed plan to use retailers also has the potential for cost reduction via the promotion of collaborative approaches with other SCs using the same retailers for their products. The model is tractable and takes a reasonable amount of time for solving the model (for example, it took approximately 20 min for the example problem) when using a commercial solver, such as LINGO.

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