The impact of two-product joint lifecycles on capacity planning of remanufacturing networks

Capacity planning in the reverse channel of closed-loop supply chains (CLSCs) involves complex issues due to the different lifecycles of product offerings in combination with the variability regarding product usage time, quality level of used products and return patterns. (Georgiadis, P., Vlachos, D., Tagaras, G., 2006. The impact of product lifecycle on capacity planning of closed-loop supply chains with remanufacturing. Production and Operations Management 15; 514–527) developed a system dynamics (SD) model to study a CLSC with remanufacturing for a single product which incorporates a dynamic capacity modeling approach. We extend this SD model for two sequential product-types under two alternative scenarios regarding the market preferences over the product-types; in the first scenario, the market is considered showing no preferences, while in the second scenario, the demand over a product-type can be satisfied only by providing units of the specific type. We study how the joint lifecycles of two product-types, entry time of the second product-type to the market and used product return patterns affect the optimal policies regarding expansion and contraction of collection and remanufacturing capacities. The results of extensive numerical investigation are tested for their statistical significance using analysis of variance (ANOVA). In the first scenario, the results show that the system performs best when the two lifecycles form a trapezoid pattern for total demand while in the second scenario, when the two lifecycles form a triangular pattern.     

A two-period game of a closed-loop supply chain

We consider a two-period closed-loop supply chain (CLSC) game where a remanufacturer appropriates of the returns’ residual value and decides whether to exclusively manage the end-of-use product collection or to outsource it to either a retailer or a third-service provider (3P). We determine that the manufacturer outsources the product collection only when an outsourcee performs environmentally and operationally better. On the outsourcees side there is always an economic convenience in managing the product returns process exclusively, independently of returns rewards and operational performance. When outsourcing is convenient, a manufacturer always chooses a retailer if the outsourcees show equal performance. Overall, the manufacturer is more sensitive to environmental performance than to operational perfomance. Finally, there exists only a small region inside which outsouring the collection process contributes to the triple bottom line.     

Simple heuristics for push and pull remanufacturing policies

Inventory policies for joint remanufacturing and manufacturing have recently received much attention. Most efforts, though, were related to (optimal) policy structures and numerical optimization, rather than closed form expressions for calculating near optimal policy parameters. The focus of this paper is on the latter. We analyze an inventory system with unit product returns and demands where remanufacturing is the cheaper alternative for manufacturing. Manufacturing is also needed, however, since there are less returns than demands. The cost structure consists of setup costs, holding costs, and backorder costs. Manufacturing and remanufacturing orders have non-zero lead times. To control the system we use certain extensions of the familiar (s, Q) policy, called push and pull remanufacturing policies. For all policies we present simple, closed form formulae for approximating the optimal policy parameters under a cost minimization objective. In an extensive numerical study we show that the proposed formulae lead to near-optimal policy parameters.     

Dynamic pricing of remanufacturable products under demand substitution: a product life cycle model

We consider a manufacturer who sells both the new and remanufactured versions of a product over its life cycle. The manufacturer’s profit depends crucially on her ability to synchronize product returns with the sales of the remanufactured product. This gives rise to a challenging dynamic optimization problem where the size of both the market and the user pool are dynamic and their current values depend on the entire history. We provide an analytical characterization of the manufacturer’s optimal pricing, production, and inventory policies which lead to a practical threshold policy with a small optimality gap. In addition, our analysis offers a number of interesting insights. First, the timing of remanufacturing activity and its co-occurrence with new product manufacturing critically depends on remanufacturing cost benefits, attractiveness of the remanufactured product and product return rate. Second, there is a small upward jump in the price of the new product when remanufacturing is introduced. Third, the manufacturer keeps the new product longer on the market as the cost of remanufacturing decreases. Fourth, partially satisfying demand for the remanufactured item is never optimal, i.e., it is satisfied either fully or not at all. Finally, user pool and inventory of returned products are substitutes in ensuring the supply for future remanufacturing.     

Product-design and pricing strategies with remanufacturing

In this paper, we consider a supply chain that consists of an original equipment manufacturer (OEM) producing new products and a remanufacturer recovering the used items. The OEM often faces a strategic dilemma when determining the degree of disassemblability of its product design, as high disassemblability decreases the OEM’s production costs as well as the remanufacturer’s recovery costs. However, high disassemblability may be harmful to the OEM in a market in which the remanufacturer is encouraged to intensify price competition with the OEM because design for high disassemblability leads to larger cost savings in remanufacturing. We first formulate a two-period model to investigate the OEM’s product-design strategy and the remanufacturer’s pricing strategy in an extensive-form game, in which the equilibrium decisions of the resulting scenarios are derived. Next, we show the thresholds that determine whether remanufacturing is constrained by collection, the thresholds for the remanufacturer’s choice of a profitable pricing strategy, and the thresholds for determining the OEM’s product-design strategy. Finally, we expand the model for a multiple-period problem to show that the main insights obtained from the two-period model can be applied.     

Multi-period reverse logistics network design

The configuration of the reverse logistics network is a complex problem comprising the determination of the optimal sites and capacities of collection centers, inspection centers, remanufacturing facilities, and/or recycling plants. In this paper, we propose a profit maximization modeling framework for reverse logistics network design problems. We present a mixed-integer linear programming formulation that is flexible to incorporate most of the reverse network structures plausible in practice. In order to consider the possibility of making future adjustments in the network configuration to allow gradual changes in the network structure and in the capacities of the facilities, we consider a multi-period setting. We propose a multi-commodity formulation and use a reverse bill of materials in order to capture component commonality among different products and to have the flexibility to incorporate all plausible means in tackling product returns. The proposed general framework is justified by a case study in the context of reverse logistics network design for washing machines and tumble dryers in Germany. We conduct extensive parametric and scenario analysis to illustrate the potential benefits of using a dynamic model as opposed to its static counterpart, and also to derive a number of managerial insights.     

Official recycling and scavengers: Symbiotic or conflicting?

Nowadays, especially in developed countries, the traditional collection of end-of-use products by scavengers has been displaced by formal waste recovery systems. However, scavenging still exists, especially in places with collection capacity shortages and/or low living standards. Besides its obvious social implications, the financial and environmental aspects of scavenging are certainly not trivial. Informal recycling of waste electrical and electronic equipment (WEEE) by scavengers not only constrains profits of the formal system. In their effort to recover the value of end-of-use products, scavengers also pollute the environment if toxic substances leak when WEEE is not properly disposed of. We investigate the impact of scavenging on the operations of the formal recovery system of WEEE, under three regulatory measures, using system dynamics methodology. By using data from a real world closed-loop supply chain that operates in Greece extended numerical experimentation revealed that a legislation incorporating scavengers into the formal waste recovery system (instead of either ignoring or prohibiting their participation) is beneficial for economical, environmental and social sustainability.     

Production planning for hybrid remanufacturing and manufacturing system with component recovery

In this paper, we address component recovery under the condition of limited resources from the OEM's (Original Equipment Manufacturer's) standpoint. We develop a linear programming model for a hybrid remanufacturing and manufacturing system for production planning problems with deterministic returns. In this paper, a data set from an OEM that both remanufactures and manufactures the products is used to demonstrate the performance of the proposed model. Subsequently, an analysis of the impact of the remanufactured product’s price and the quantity of returns on revenue and total cost will be discussed. We have found that uncertain factors of manufacturing influence the profit and uncertain factors of remanufacturing influence the production planning, such as the rate of the yield on component remanufacturing and the quantity of returns.     

再制造能力有限的多产品混合系统库存决策

为确定各产品的制造与再制造策略,对再制造能力有限的多产品混合系统进行研究.在系统中,对多种产品进行制造和再制造.每种产品在顾客使用后都会以恒定速率返回,但因再制造能力有限,有些产品无法用于再制造而被处置.每种产品需求恒定且由服务性产品来满足,服务性产品由制造品和再制造品组成,不允许缺货.在一次制造准备和至少一次再制造准备策略下构建了库存决策模型,利用拉格朗日乘数法和贪婪算法分别确定了各产品的再制造顺序和再制造比率.并当再制造比率一定时,给出了再制造准备次数为正整数时各产品制造与再制造策略的求解程序,得到了各产品制造和再制造批量、再制造准备次数等求解公式.最后,应用算例对模型及求解方法进行了验证.