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Environmental legislation and customer expectations increasingly force manufacturers to take recovery of used products into account in their production and inventory management. One of the areas concerned is production planning with returned products remanufacturing. In this paper, we discuss the optimal decision for a joint manufacturing and remanufacturing system in a multi-period horizon, including manufacturing decision, remanufacturing and disposal decisions of the returned product. Setup costs are considered for the manufacturing and disposal activities. For an n-period model, we derive an optimal solution structure for the three activities, where the solution parameters can be computed by dynamic programming approach.

The return of used products (cores) is the beginning of remanufacturing. Although an appropriate pricing policy can effectively manage the returns, a static pricing policy cannot match the returns and demands because of the high uncertainties in both sides, which in turn results in high inventory cost or lost-sale cost. In this paper, we apply a dynamic pricing policy commonly used in retail setting to the core acquisition management in remanufacturing and study the pricing problem for used products with the objective of minimizing average cost over an infinite horizon. We formulate the pricing problem as a continuous-time Markov decision process and characterize the structural properties of the optimal policy. We also conduct a numerical study to investigate the benefit of dynamic pricing.

This paper adds to the growing remanufacturing literature by investigating a collaborative model in which the manufacturer serves as the remanufacturer's distributor while selling its own product. The paper extends the collaborative model that we have studied previously by characterizing it as a channel power structure under which the manufacturer plays the leader role in the collaboration. Furthermore, the paper compares this collaborative model with a competitive model in which the manufacturer competes with the remanufacturer in the market on pricing, sales volume and profit and finds that even if the manufacturer chooses to collaborate with the remanufacturer, it does not give up its market position; the manufacturer keeps the price of its product unchanged as the remanufactured product becomes increasingly acceptable to the consumer, and its product's sales volume remains unchanged in both models. Finally, this paper observes that the collaborative model benefits the manufacturer more than the competitive model, whereas the competitive model benefits the remanufacturer more than the collaborative model. Obviously, if collaboration benefits both of the manufacturer and remanufacturer, they will choose to collaborate, and the manufacturer will transfer part of its profit to the remanufacturer, but if competition brings them more profit, they will choose to compete in the market, and the remanufacturer will transfer part of its profit to the manufacturer.

In this paper, we address the scheduling issues in a class of maintenance, repair and overhaul systems. By considering all key characteristics such as disassembly, material recovery uncertainty, material matching requirements, stochastic routings and variable processing times, the scheduling problem is formulated into a simulation optimization problem. To solve this difficult problem, we developed two hybrid algorithms based on nested partitions method and optimal computing budged allocation technology. Asymptotic convergence of these two algorithms is proved and numerical results show that the proposed algorithms can generate high quality solutions which outperform the performance of many heuristics.

Nowadays, pricing and remanufacturing problems under uncertain markets have gained increasing attention from both industrial and academic fields. In the literature, it is generally assumed that all the channel members are risk-neutral, ignoring the influences of channel members’ risk attitudes in the face of dynamic market. This paper focuses on a pricing problem in a closed-loop supply chain (CLSC) with two competitive risk-sensitive retailers under uncertain environment. The uncertainty is associated with the recycling costs, consumer demands and remanufacturing costs. Due to the dynamic market, supply chain managers may be unable to collect enough historical data to estimate these demands and costs when making pricing and remanufacturing decisions. In such cases, experts’ estimations are usually employed to describe these uncertain parameters. To deal with these human estimations, an uncertainty theory-based model is proposed. Based on the equilibrium results, how the retailers’ risk sensitivity and human estimations (uncertain degrees) affect the prices and profits is analyzed. It is found that both the retailers will get lower profits while the manufacturer will gain more profit when either of the two retailers becomes more risk-averse. We also find that a higher level of uncertainty in the supply chain will induce a higher collecting rate.

In recent times, sustainability has become more important for businesses. Accordingly, product remanufacturing has emerged as an interesting topic, as it is generally considered as a profitable and environmentally friendly end-of-use management option for several products. While extant literature on remanufacturing has comprehensively studied the topic of outsourcing, it has failed to recognize that retailers also have the flexibility to engage in remanufacturing. However, in recent years, several brand name retailers have established remanufacturing operations. The following question arises: Should original equipment manufacturers (OEMs) outsource their remanufacturing operations to their retailers? To answer this question, two models are developed in which an OEM interacts with an independent retailer on remanufacturing operations with the option to either remanufacture all products in-house (Model M) or outsource remanufacturing to their retailer (Model R). The result shows that although model M potentially facilitates greater economic, social, and environmental sustainability, it has costs for the retailer. Finally, a revenue-sharing contract is proposed to achieve a “win-win-win” outcome that has economic, social, and environmental benefits for all parties.

The remanufacturing industry is experiencing a gradual increase in international trade. Accordingly, manufacturers are encountering a multitude of regulations in this cross-border trade of remanufactured products, such as import prohibitions/bans, environmental regulations, and tariff barriers. In this paper, we investigated the implications of exporting remanufactured products to the international market with or without trade regulations. Our analysis reveals that, although the international market for remanufacturing invariably benefits the manufacturer, trade regulations are a disadvantage to remanufactured exports. Thus, while the quality of remanufactured products increases, the adverse effect of trade regulations could be weakened. Additionally, we reveal that trade regulations may be detrimental to the environment with a higher rate of used core collection and disposal impact. Thus, policymakers should take care to regulate the international market for remanufactured goods rather than implementing a one-size-fits-all solution.

This paper considers a dual-channel closed-loop supply chain (CLSC) consisting of a manufacturer who wholesales new products through the traditional retail channel and distributes remanufactured products via a direct (online) channel established by himself. Two dynamical Stackelberg game models are developed based on the assumption that the retailer is an adaptive player, and the manufacturer is a bounded rational player who may adopt a delay decision. The existence and locally asymptotic stability of the Nash equilibrium are examined. Moreover, the impacts of key parameters on the complexity characteristics of the models and the performance of chain members are studied by numerical simulation. The results reveal that the excessively fast price adjustment speeds of the manufacturer, the larger consumers’ discount perception for the remanufactured products, and the consumers’ preference for the direct channel have a strong destabilizing effect on the Nash equilibrium’s stability. Furthermore, the delay decision implemented by the manufacturer could be a stabilizing or destabilizing factor for the system. The manufacturer will tolerate a considerable profit reduction while the retailer gains more profits when the dual-channel CLSC system enters periodic cycles and chaotic motions.

This paper documents the basic manufacturing philosophies and methodologies utilized for the design and implementation of a Lean Manufacturing remanufacture cell. Remanufacture deals with overhauling or reworking products that have been in service and need modification in order to continue to be serviceable. This remanufacturing cell implementation is the first cell of an eighteen-cell manufacturing and remanufacturing system. A systematic detailed case study is utilized as a Lean Production example and proves the flexibility of Lean Manufacturing to be adaptive while being cost effective in the remanufacture arena. This study provides key insights into a concept and strategy for implementing Lean Production thinking — cellular manufacturing. Most factories need significant assistance in understanding how to make Lean Production work; this paper provides many insights into both the theory and application of cellular manufacturing/assembly systems for remanufacture.

This chapter introduces the basic working principles of genetic algorithm (GA). This method was tested on typical used products collection problem in the context of remanufacturing. It was observed that genetic algorithm was able to find the shortest travel plan, while keeping the fuel consumption rate at the lowest possible level. Furthermore, GA was used to update the finite element (FE) model to better reflect the measured data. The results obtained indicated that GA was able to successfully update the FE model resulting in better reflection of the measured data.

Hydraulic cylinder remanufacture process has been analyzed and case properties have been extracted, then a case-based reasoning cost estimating model of hydraulic cylinder remanufacturing was built. The three methods, namely, equal weight (EW), gradient descent method (GDM) and analytic hierarchy process (AHP) are used to compute the weights of case attributes. The cost estimating of three different models are compared. The fidelity of CBR model using AHP weights is better than that of the other two models. By solving new projects using experience from historical cases, it is found that CBR was an effective method in cost estimating of hydraulic cylinder remanufacturing.

The current research sets the BP neural network and CBR as factors of engineering machinery hydraulic cylinder remanufacturing cost prediction. Take the differences between the new product manufacturing and remanufacturing and the process of hydraulic cylinder remanufacturing into consideration, we extract 10 feature factors and case attributes and establish BP prediction model and CBR model respectively. The comparison of two models indicates that the BP model and CBR model are both feasible ways to estimate the manufacturing cost of engineering machinery hydraulic cylinder and the BP model is more accurate. Study provides a feasible method for engineering machinery hydraulic cylinder remanufacturing production cost prediction, as well as effective measures for remanufacturing economic efficiency.

A method of CNC remanufacturing for machining tools has been introduced. The scheme of remanufacturing for a vertical lathe has been elaborated in detail. Including the replacement of electric spindle and electric tool rest, the selection of NC system, and achieving the semi-closed loop servo drive, etc. The scheme is proved to be feasible in the way of green evaluation from the technical and economic aspects, based on a general green evaluation method.