Assessing the benefits of remanufacturing option under one-way substitution and capacity constraint

In this article, we investigate the profitability of remanufacturing option when the manufactured and remanufactured products are segmented to different markets and the production capacity is finite. It is assumed that remanufactured products can be substituted by the manufactured ones. A single period profit model under substitution is constructed to investigate the system conditions under which remanufacturing is profitable. We present analytical findings and computational results to show profitability of remanufacturing option under substitution policy subject to a capacity constraint of the joint manufacturing/remanufactruing facility

Disposition Choices Based on Energy Footprints instead of Recovery Quota

This paper addresses the impact of disposition choices on the energy use of closed-loop supply chains. In a life cycle perspective, energy used in the forward chain which is locked up in the product is recaptured in recovery. High quality recovery replaces virgin production and thereby saves energy. This so called substitution effect is often ignored. Governments worldwide implement Extended Producer Responsibility (EPR). Policies are based on recovery quota and not effective from an energy point of view. This in turn leads to unnecessary emissions of amongst others CO2. This research evaluates current EPR policies and presents six policy alternatives from an energy standpoint. The Pareto-frontier model used is generic and can be applied to other closed loops supply chains under EPR, exploiting the substitution effect. The measures modeled are applied to five WEEE cases. We discuss results, pros an cons of various alternatives and complementary measures that might be taken.extended producer responsibility;disposition;energy perspective;substitution effect;government policies;Pareto efficiency

Selection of return channels and recovery options for used products

Due to legal, economic and socio-environmental factors, reverse logistics practices and extended producer responsibility have developed into a necessity in many countries. The end results and expectations may differ, but the motivation remains the same. Two significant components in a reverse logistics system -product recovery options and return channels - are the focus of this thesis. The two main issues examined are allocation of the returned products to recovery options, and selection of the collection methods for product returns. The initial segment of this thesis involves the formulation of a linear programming model to determine the optimal allocation of returned products differing in quality to specific recovery options. This model paves the way for a study on the effects of flexibility on product recovery allocation. A computational example utilising experimental data was presented to demonstrate the viability of the proposed model. The results revealed that in comparison to a fixed match between product qualities and recovery options, the product recovery operation appeared to be more profitable with a flexible allocation. The second segment of this thesis addresses the methods employed for the initial collection of returned products. A mixed integer nonlinear programming model was developed to facilitate the selection of optimal collection methods for these products. This integrated model takes three different initial collection methods into consideration. The model is used to solve an illustrative example optimally. However, as the complexity of the issue renders this process ineffective in the face of larger problems, the Lagrangian relaxation method was proposed to generate feasible solutions within reasonable computational times. This method was put to the test and the results were found to be encouraging

Optimal Decision Making for Capacitated Reverse Logistics Networks with Quality Variations

Increasing concerns about the environmental impact of production, product take-back laws and dwindling natural resources have heightened the need to address the impact of disposing end-of-life (EOL) products. To cope this challenge, manufacturers have integrated reverse logistics into their supply chain or chosen to outsource product recovery activities to third party firms. The uncertain quality of returns as well as uncertainty in return flow limit the effectiveness of planning, control and monitoring of reverse logistics networks. In addition, there are different recovery routes for each returned product such as reuse, repair, disassembling, remanufacturing and recycling. To determine the most profitable option for EOL product management, remanufacturers must consider the quality of returns and other limitations such as inventory size, demand and quantity of returns. The work in this dissertation addresses these pertinent aspects using two models that have been motivated by two remanufacturing facilities whereby there are uncertainties in the quality and quantity of return and capacitated inventories. In the first case, a disposition decision making model is developed for a remanufacturing process in which the inventory capacity of recoverable returns is limited and where there\u27s a constant demand to be met, for remanufactured products that meet a minimum quality threshold. It is assumed that the quality of returns is uncertain and remanufacturing cost is dependent on the quality grade. In this model, remanufacturing takes place when there is demand for remanufactured products. Accepted returns that meet the minimum quality threshold undergo the remanufacturing processes, and any unacceptable returns are salvaged. A continuous time Markov chain (CTMC) is presented as the modeling approach. The Matrix-Geometric solution methodology is applied to evaluate several key performance metrics for this system, to result in the optimal disposition policy. The numerical study shows an intricate trade-off between the acceptable quality threshold value and the recoverable product inventory capacity. Particularly, there are periodic system starvation whenever there is a mis-match between these two system metrics. In addition, the sensitivity analysis indicates that changes to the demand rate for remanufactured products necessitates the need to re-evaluate the existing system configuration. In the second case, a general framework is presented for a third party remanufacturer, where the remanufacturer has the alternative of salvaging EOL products and supplying parts to external suppliers, or remanufacture the disassembled parts to \u27as new\u27 conditions. The remanufacturing processes of reusable products and parts is studied in the context of other process variables such as the cost and demand of remanufactured products and parts. The goal of this model is to determine the return quality thresholds for a multi-product, multi-period remanufacturing setting. The problem is formulated as a mixed integer non-linear programming (MINLP) problem, which involves a discretization technique that turns the problem turns into a quadratic mixed integer programming (QMIP) problem. Finally, a numerical analysis using a personal computer (PC) remanufacturing facility data is used to test the extent to which the minimum acceptance quality threshold is dependent on the inventory level capacities of the EOL product management sites, varying operational costs and the upper bound of disposal rate

Revenue management for multiple product recovery options : a triangulation approach

In recent times large numbers of end-of-use/end-of-life returns have been the result of the increasing pressure from environmental legislations, particularly the directive on Waste Electrical and Electronic Equipment (WEEE) in the European Union. These returns incur acquisition costs and take-back operation costs regarded as a sunk cost by many industries. Thus, returned/recovered product valuation and marketing issues become crucial factors for survival and profitability of many firms in various sectors in today’s competitive world. The research undertaken is relevant as pricing and revenue management for recovered products. Indeed, this theme is considered as a niche research and the fifth phase (prices and markets) of the evolution of closed loop supply chain research. Hence, it has been noted as one of the most critical research areas in quantitative modelling for reverse logistics and closed loop supply chain management studies. The research area is in its early stage because it can be seen that only a handful of articles have been published in peer reviewed international journals, exploring a pricing and marketing decision of recovered products. Hence, there are significant opportunities to conduct pricing and revenue management research in reverse logistics, particularly with regard to multiple recovery options.The primary objective of this research work is to formulate three pricing models by using a non-linear programming approach to determine optimal profit-maximising acquisition prices and selling prices, together with UK-based case studies in the mobile phone and computer recycling businesses. Moreover, this research aims to formulate two simulation models based on these case companies by investigating the impact of the uncertainty element in terms of return quantity and reprocessing time on firm’s profit. The triangulation approach is employed, specifically the multilevel model comprising case studies, questionnaire survey, and empirical quantitative models in order to address the principal research questions i.e. “What are optimal acquisition prices of received mobile phones and optimal selling prices of reprocessed handsets?”, “What are optimal selling prices of reprocessed computers?”, and based on the total profit, “What if the model's parameters change?”The contribution of this research covers the generation of pricing and simulation models that are suitable for the recycled mobile phone and computer sector. The literature review discovers that the research on this subject lacks considerations of multiple recovery options, return rate and demand rate as exponential functions, recovery capacity limitation, product substitution policy, the element of uncertainty in terms of return quantity and reprocessing time, and multiple time periods. Hence, this research fulfils six main research gaps in academic literature as follows. First, this study takes multiple recovery options into account. Second, return and demand rate are modelled as an exponential function. Third, pricing and simulation models cope with a limit to recovery capacity. Fourth, models with product substitution policy are investigated. Fifth, the element of uncertainty in terms of return quantity and reprocessing time is added into proposed models. Finally, this study proposes models with multiple time periods.The results from this research work support current pricing and revenue management research and most importantly, the results generated from these proposed models can enhance managers’ decision making in recovery operations and reverse logistics

Optimal remanufacturing strategies in name-your-own-price auctions with limited capacity

We study optimal pricing and production strategies faced by a manufacturer in a remanufacturing/manufacturing system. In the reverse channel, returns are collected under a name-your-own-price (NYOP) bidding mechanism. The manufacturer has a limited capacity to produce new and remanufactured products. We characterize the optimal decisions of the consumers and the manufacturer. We find that under the NYOP mechanism, the manufacturer׳s optimal strategies mainly depend on the bidding cost, the cost saving of remanufacturing, the production capacity, and the market scale. In addition, when remanufacturing needs more capacity than manufacturing , the manufacturer may adopt pure manufacturing strategy without remanufacturing. We also compare this mechanism with the traditional list-price mechanism and find that the manufacturer prefers the NYOP mechanism under the conditions of a low reverse market share, a high manufacturing cost, a sufficient capacity, or a low capacity requirement of remanufacturing. Numerical studies investigate the effect of key parameters on the manufacturer׳s profit and some managerial insights are obtained

Substitution in a hybrid remanufacturing system

AbstractIncreasing legislative and societal pressures are requiring manufacturers to operate more sustainably and to take responsibility for the fate of their goods after they have been used by consumers. A hybrid remanufacturing system, in which newly produced and remanufactured used goods are sold on separate markets but also act substitutes for each other, is described and modelled using a semi-Markov decision process. The model provides an optimal policy, which specifies production, remanufacturing and substitution decisions. The model is used to explore the properties of this hybrid remanufacturing system, and in particular, the managerial implications associated with upward and downward substitution

Remanufacturing as a potential means of attaining sustainable industrial development in Indonesia

Remanufacturing industries account for a considerable share of small medium enterprises (SMEs) in both developed and developing countries. There is an urgent need for a sustainable manufacturing strategy for remanufacturing SMEs in developing countries in order for them to gain global market competitiveness through minimizing environmental impact while maximizing the economic and social benefits of SME manufacturing activities. This research uses Indonesian remanufacturing SMEs as a case study for sustainable manufacturing in developing countries