Dynamic buy-back for product recovery in end-of-life spare parts procurement

The efficient supply of spare parts is of prime concern for original equipment manufacturers (OEM). While manufacturing the parent product, spare parts can be sourced efficiently by using existing manufacturing facilities. This situation completely changes once the original equipment manufacturer ceases production of the parent product. In addition to traditional spare parts sources in the form of final order and remanufacturing, the option to buy back parts or products provides a viable alternative in the end-of-life phase. This can prevent the OEM from fulfilling his spare parts availability obligation or increase his ability to remanufacture. Current practice in industry is, on the one hand, to offer trade-in campaigns to acquire functional products from customers by giving substantial discounts on a new-generation product. On the other hand, trade-in rebates are given when customers return their broken parts in exchange for spare parts. We propose the consideration of a third option, i.e. to buy back broken products in order to improve control of both demand for spare parts and supply of recoverable parts. This contribution seeks to assess the potential benefit of buy-back strategies in contrast to both traditional sourcing and trade-in campaigns for different settings regarding information availability and buy-back flexibility. For each situation, a MILP formulation is presented, and in a numerical study we analyse the circumstances under which the buy-back of broken products is especially beneficial for the OEM.     

Quantity decisions in a supply chain with early returns remanufacturing

Consider a supply chain where the retailer faces a stochastic demand and orders from the supplier, while the supplier manufactures new products and also remanufactures early returns to meet the order. The order and manufacturing quantity decisions are studied under three decentralised cases: (1) the Stackelberg case, where the manufacturing quantity is determined by the supplier after realising the order quantity from the retailer; (2) the Nash case, where the manufacturing and order quantities are determined simultaneously; (3) the inaccessible return information case, where the retailer does not have the distribution information of upstream returns. We find that in the Stakelberg case the order and manufacturing quantities are larger than in the inaccessible return information case, and the profits for the supplier and retailer are also higher. In contrast, the quantities and profits in the Nash case are the lowest of the three cases when the returns are negatively correlated to the demand. The centralised system is also explored by solving a two-step dynamic program. Computational results are reported to show the effects of system parameters.     

Reverse Logistics: a stochastic EOQ-based inventory control model for mixed manufacturing/remanufacturing systems with return policies

This paper focuses on mixed manufacturing/remanufacturing systems, where manufacturing or purchase of new items integrates product reuse or remanufacturing, with the purpose to achieve a complete and timely demand satisfaction. We formulate a stochastic Economic Order Quantity (EOQ)-based inventory control model for a mixed manufacturing/remanufacturing system. The model is intended to identify the need of placing a manufacturing/purchasing order, to avoid the occurrence of stock-out situations. We then formulate a total cost minimisation problem, to derive the optimal return policy, this latter being a financial incentive paid to customers to increase the flow of returned items. The model developed is investigated through simulations, in order to assess the effect of stochasticity (of demand, return fraction and return delay) on the optimal return policy of the system; then, it is validated through a case study, to derive indications concerning its practical application in real cases. Our study ultimately provides a framework for practitioners to establish EOQ policies in reverse logistics contexts and to evaluate the opportunity of establishing a return policy in those contexts.     

Last Time Buy and control policies with phase-out returns: a case study in plant control systems

This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This article, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defect returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this article explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the non-stationary nature of the problem. We have to consider subintervals within the total planning interval to optimise both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove to be efficient and close to optimal when validated. The resulting control policies in the case study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimising the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The article concludes by mapping a number of extensions for future research, as it represents a larger class of problems.     

Implementing just-in-time philosophy to reverse logistics systems: a review

Just-in-time (JIT) and reverse logistics are two important philosophies. Coincidentally, both are related to reducing the impact on the environment. However, they are sometimes in conflict with each other. The former focuses on moving the materials smoothly which require a stable demand and supply, but the latter is weak in terms of predicting how many returned products will be processed. Therefore, there is a need to investigate the impact of JIT to reverse logistics systems. After an extensive literature review based on a model developed for this purpose, different functions, namely reverse logistics structure, process model, product life cycle, information system model, and JIT performance, have been identified that have great impact on integrating JIT with reverse logistics. In short, a process model with JIT can have a better control on cost and efficiency of reverse logistics activities, and product life cycle management with JIT helps to design the product that consider the reverse activities in various process models. An information system can support both process model and product life cycle management for JIT reverse logistics. Details are presented in this paper.     

Remanufactured products purchase intentions and behaviour: Evidence from Malaysia

One of the greatest threats to widespread diffusion of closed-loop supply chain (CLSC) practices in support of consumer goods is the lack of consumer acceptance of remanufactured products. Although the preponderance of extant CLSC research historically focused on product reclamation and remanufacturing practices, consumer acceptance of remanufactured products is now receiving more attention. However, significant gaps in the literature remain to include examining actual consumer behaviour in the presence of alternative offerings. Using theory of planned behaviour and data gathered from Malaysia, this research addresses these gaps by examining how consumer attitude, subjective norms and perceived behavioural control with regard to purchasing remanufactured products affect consumer intention to purchase remanufactured consumer electronic products. Then, actual purchase behaviour is compared with purchase intentions to determine if consumers followed through with their intentions. Findings suggest that consumers are most apt to purchase energy-efficient offerings regardless of their original intentions.     

Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response

This paper proposes a stochastic linear mixed-integer programming model for integrated decisions in the preparedness and response stages in pre- and post-disaster operations, respectively. We develop a model for integrated decisions that considers three key areas of emergency logistics: facility and stock prepositioning, evacuation planning and relief vehicle planning. To develop a framework for effective relief operations, we consider not only a cost-based but also an equity-based solution approach in our multiple objectives model. Then a normalised weighted sum method is used to parameterise our multiple objective programming model. This paper suggests a compromise between the cost, and the equity of relief victims. The experiments also demonstrate how time restrictions and the availability of relief vehicles impact the two objective functions.     

Optimal purchase and selling strategy for wholesaler of produce: sorted or unsorted selling?

Produce (e.g. fruit and vegetable) varies in quality when it is picked from plants. Then a produce wholesaler has two sales strategies: (1) unsorted selling (US), i.e. selling the produce to the market at one price and (2) sorted selling (SS), i.e. pre-sorting the produce into different grades by quality and selling them at different prices. When the SS strategy is adopted, the demands of the different grades are uncertain and substitutable. In this paper, we study the joint optimal purchase and sales strategy for selling mixed quality produce to customers with heterogeneous quality preferences. We first derive the optimal purchase policies under the two strategies and then identify the conditions under which the SS or US strategy is optimal. We show that the optimal sales strategy is determined by the marginal purchase and sorting cost and the fixed investment cost, the overall quality level of the produce, and the substitution rate for the high-quality and low-quality produce. This finding differs from the conventional wisdom that the SS strategy is optimal in the produce retail business. Finally, we conduct numerical studies based on real-world data to generate managerial insights from the analytical findings.     

Optimal pricing and trade-in policies in a dual-channel supply chain when considering market segmentation

Many companies are implementing trade-in programmes through multiple channels. This may ultimately lead to fiercer channel conflict and competition. Few studies have explored firms’ optimal trade-in policies in such an environment. To fill the gap, we build a theoretical model that captures the features of a dual-channel situation in which a manufacturer implements a trade-in programme through retail and direct channels simultaneously. Compared with the case in which there is no trade-in rebate, the results show that a trade-in programme can intensify or mitigate the double marginalisation effect if the retailer can initially decide the trade-in rebate in the retail channel. This significantly relies on market segmentation. However, when the retailer cannot decide the trade-in rebate in the retail channel, the trade-in programme aggravates the double marginalisation effect. Second, the trade-in rebate offered by the retailer may be higher than the subsidy offered by the manufacturer, as long as the retailer can autonomously decide the trade-in rebate in the retail channel. Furthermore, we find that both the manufacturer and retailer prefer to obtain the right to autonomously decide the trade-in rebate in the retail channel, but the supply chain prefers that the manufacturer do it. Some numerical examples are provided to further explain these outcomes.     

Quality-driven recovery decisions for used components in reverse logistics

Reverse logistics has emerged as a promising strategy for enhancing environmental sustainability through remanufacturing, reusing, or recycling used components. It is crucial to pursue quality-driven decision-making for component recovery because quality is a dominant factor for component salvage value and its recoverability. To maximise the profit from component recovery, a quality-driven decision model was proposed in this study. Remaining useful life (RUL) was utilised as a measure of quality in the proposed model, where conditional RUL distribution was predicted by utilising both the failure data and condition monitoring data based on a proportional hazard model. Under RUL uncertainty, an interval decision-making approach was developed to suggest recovery strategies for the decision-makers to identify a satisfactory solution according to their risk preferences. Compared to the existing approaches for quality-driven recovery decision-making based on RUL prediction, this work provides a more accurate and powerful approach to managing and mitigating decision risk. Numerical experiments demonstrated the effectiveness and superiority of the proposed model.     

Order timing strategies in a single-supplier,multi-retailer system

The timing of retailer order placement is an important factor in supply chain performance in systems with uncertain end-customer demands. Retailers often prefer short order lead times, which permits the resolution of demand uncertainty prior to order placement, and reduces the risks associated with excess inventory. Suppliers, in contrast, prefer long lead times, in order to match supply output with retailer demand. These conflicting preferences create tension between a supplier and retailers regarding order timing preferences. This paper considers order timing preferences within a strategic framework involving a supplier and one of its retailers in a multiple-retailer system. We identify and explore several mechanisms a supplier can use within this framework to induce early retailer order placement and improve expected cost performance.     

An empirical study of impacts of production mix,product route efficiencies on operations performance and profitability: a reverse logistics approach

This research studies the impact of two reverse logistics business strategies on profitability of the firm through operations management (OM). The study is employed on scrap steel industry. The first strategy is production mix efficiency (PME), which is involved in the process of producing goods. The second strategy is product route efficiency (PRE), which engages in the transportation of goods. Our finding indicates that OM alone does not have a positive impact on profitability. However, the two strategies have a positive effect on profitability, which provides a potential answer to firms trying to improve profitability.     

Optimal collection and remanufacturing decisions in reverse supply chains with collector’s imperfect sorting

We consider a reverse supply chain comprising two independent companies: the collector and the remanufacturer. The collector is responsible for sorting the collected used products and then transporting the ‘remanufacturable’ items to the remanufacturer. As sorting is not perfectly accurate, the misclassification errors affect the optimal decisions in the reverse supply chain. We focus on the optimal collection quantity for the collector and the optimal order quantity for the remanufacturer using game theory under both deterministic and uncertain demand. We characterise the optimal solution and show that under certain conditions, the remanufacturer should allow the collector to transport more ‘remanufacturables’ than the order quantity. We then examine the case where both the collector and the remanufacturer belong to a single company with centralised decision-making and compare the optimal collection quantities under both structures of the reverse supply chain.     

Closed-loop supply chains of reusable articles: a typology grounded on case studies

Reuse practices contribute to the environmental and economical sustainability of production and distribution systems. Surprisingly, reuse closed-loop supply chains (CLSC) have not been widely researched for the moment. In this paper, we explore the scientific literature on reuse and we propose a definition for reusable articles and a typology integrating different categories of articles (transportation items, packaging materials, tools) under the term ‘reusable articles’. Our definition shows how reusable articles are different from other types of recovery, such as remanufacturing or recycling. We also point out specific research needs for those articles. We have based our results on a set of case studies developed in real industrial settings, which have also been contrasted with cases available in the existing literature.     

An evolutionary algorithm for a new multi-objective location-inventory model in a distribution network with transportation modes and third-party logistics providers

This paper proposes a multi-objective optimisation algorithm for solving the new multi-objective location-inventory problem (MOLIP) in a distribution centre (DC) network with the presence of different transportation modes and third-party logistics (3PL) providers. 3PL is an external company that performs all or part of a company’s logistics functions. In order to increase the efficiency and responsiveness in a supply chain, it is assumed that 3PL is responsible to manage inventory in DCs and deliver products to customers according to the provided plan. DCs are determined so as to simultaneously minimise three conflicting objectives; namely, total costs, earliness and tardiness, and deterioration rate. In this paper, a non-dominated sorting genetic algorithm (NSGA-II) is proposed to perform high-quality search using two-parallel neighbourhood search procedures for creating initial solutions. The potential of this algorithm is evaluated by its application to the numerical example. Then, the obtained results are analysed and compared with multi-objective simulated annealing (MOSA). It is concluded that this algorithm is capable of generating a set of alternative DCs considering the optimisation of multiple objectives, significantly improving the decision-making process involved in the distribution network design.     

Inventory management in a lateral collaborative manufacturing supply chain: a simulation study

Due to global competition, firms are seeking more effective supply chain (SC) collaboration in order to provide quality products with less cost, at the right time and in the right quantity. The present study examines manufacturing SC collaboration on the basis of holding cost, backorder cost and ordering cost. The types of collaboration examined are vertical, horizontal and lateral collaboration. This research emphasises lateral collaboration by determining the impact of inventory policies ((s, S) and (s, Q) inventory policies) on SC performance. For better understanding, a conceptual model is provided that is supported by a numerical example. As the study of SCs is complex in nature, a simulation approach has been employed to show the impact of lateral collaboration on performance measures such as the total cost, which is the sum of several cost components: inventory holding cost, backorder cost and ordering cost. The research is based on two manufacturing SCs where the manufacturer is taken as the collaborative node. To allow more clarity, a separate study on each cost component has been conducted. The laterally collaborative SC was simulated on ARENA 9.0, a simulation package. The results show that the efficacy of lateral collaboration outperforms horizontal collaboration due to having the individual SC members at more liberty to make decisions.     

Joint pricing and inventory strategies in a supply chain subject to inventory inaccuracy

This paper focuses on pricing strategies, inventory policies for a supply chain when Radio Frequency Identification (RFID) technology is adopted to cope with inventory inaccuracy. The supply chain consists of one supplier and one retailer, in which the RFID tag price is shared between the supplier and the retailer. We present and compare the performance differences between a wholesale price contract and a consignment contract when the retailer is the Stackelberg leader and the supplier is the follower. Based on the optimal pricing and inventory decisions, an interesting observation of contract selection is that there are two critical values of inventory available rate such that when the inventory availability is less than the lower value, both the supplier and the retailer prefer a consignment contract; when the inventory availability is greater than the upper value, a wholesale price contract is their best choice; when the inventory availability is between the two values, the supplier prefers a wholesale price contract and the retailer prefers a consignment contract. Additionally, there exist threshold values of RFID tag price and sharing rate to determine the contract preference for the retailer. Furthermore, the profits of both the supplier and the retailer are independent of the RFID tag price sharing rate in a wholesale price contract, and the supplier has the incentive to invest in RFID tag cost in a consignment contract.     

Zero inventory and firm performance: a management paradigm revisited

According to the ‘zero inventory’ paradigm, inventory reflects waste and should be eliminated in order for performance to rise. In this study, we investigate the effect of inventory holding on firm performance, analysing 3057 firm years of data. Interpreting performance as a function of inventory, results show that firms with the lowest inventory have the worst performance (and vice versa). When understanding inventory as a function of performance, results indicate that low-performing firms carry the least inventory, whereas high-performing firms have the highest stocks. Besides questions of causality, our results do not support a paradigm which suggests that firms should move toward zero inventory.     

Managing information and supplies inventory operations in a manufacturing environment. Part 1: An action research study

In the first part of this research study, we describe the application of the action research method in the nuclear fuel manufacturing industry to process information and to develop a lean operating supplies inventory program. The motivation for our work stems from the interaction we had with AREVA Richland, the nuclear reactor fuel production site located in the state of Washington to investigate the important role that information processing and maintenance inventory play in keeping the production process functioning on schedule. AREVA's data systems are not well documented. Hence, designing a methodology to obtain good data and perform any validity checks was critical for the company. Additionally, the importance of meeting delivery schedules to nuclear power plants throughout the world cannot be overestimated. Late deliveries of fuel can easily destroy the precise schedules for power plant outages designed to minimise plant downtime and maximise electric power output. Therefore, AREVA cannot tolerate significant production schedule deviations. Maintenance items play a key role in ensuring that production schedules are met. AREVA has about $700,000 tied up in maintenance inventory at their Washington state plant. Hence driving this investment down, while maintaining a high fill-rate, is crucial. Through the deployment of process maps, failure mode effect analysis and cause-and-effect diagram, we managed an action research project that helped process information flow along the company's supply chain and generated a 27% reduction in inventory relative to the system that was currently in place at AREVA.     

Optimal manufacturing policy in a reverse logistic system with dependent stochastic returns and limited capacities

The stochastic models of systems with reverse logistics usually assume that the quantity of products returned is independent of sales. This hypothesis is obviously not true and can lead to suboptimal production policies. In this paper a new sales-dependent returns model is described. In this model, the returns depend on the useful life of the products sold and on the probability of an end-of-life product being returned. A Markov decision problem is formulated in order to obtain the optimal manufacturing policy. A numerical example is provided to illustrate the use of the defined model. An approximated Markov decision model is defined where the optimal policy is easily obtained. The optimal policies of the original and the approximated models are compared.