The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

Production planning and control of closed-loop supply chains

More and more supply chains emerge that include a return flow of materials. Many original equipment manufacturers are nowadays engaged in the remanufacturing business. In many process industries, production defectives and by-products are reworked. These closed-loop supply chains deserve special attention. Production planning and control in such hybrid systems is a real challenge, especially due to increased uncertainties. Even companies that are engaged in remanufacturing operations only, face more complicated planning situations than traditional manufacturing companies.We point out the main complicating characteristics in closed-loop systems with both remanufacturing and rework, and indicated the need for new or modified/extended production planning and control approaches. An overview of the existing scientific contributions is given. It appears that we only stand at the beginning of this line of research, and that many more contributions are needed and expected in the future.closed-loop supply chains;Production planning and control

An integrated decision support framework for remanufacturing in the automotive industry

In today\u27s global economy, firms are seeking any and every opportunity to differentiate from competitors by reducing supply chain costs and adding value to end customers. One increasingly popular option, under growing consumer awareness and increasing legislation, is to reintegrate returned products into the supply chain to achieve economic benefits as well as improve sustainability. An important class of such reverse goods flows has to do with remanufacturing (reman), which refers to activities that restore returned products ( cores ) or their major modules to operational condition for using in place of new product or distributing through other channels (e.g., spare parts). While opportunities abound, some key complications reported in the literature include: 1) difficulty in timing the launch of reman product (while accounting for uncertainties associated with product life-cycle demand and core supply), 2) difficulty with capacity planning for remanufacturing (while accounting for the fact that volumes can be low and that facilities/lines should target multiple product families for economies of scale), and 3) operational difficulties in maintaining efficiencies in production planning and control of remanufacturing activities. These difficulties are mostly attributable to limited visibility and higher levels of uncertainty in reverse logistics (in comparison with forward logistics). Despite advances in the remanufacturing literature in the last two decades (both in the academic literature and practitioner community), there is no integrated decision support framework that can guide companies to successful launch and execution of remanufacturing operations. This is particularly true for companies that engage in both original equipment (OE) service as well as the independent after-market (IAM) in the automotive industry. This research aims to address these limitations by developing a decision support framework and necessary models for effective remanufacturing in the automotive industry. At the strategic level, we propose a unified approach to explicitly model and address issues of capacities as well timing the launch of remanufacturing programs for new product. We derive the optimal remanufacturing policy and extensively studied the drivers of cost-effective remanufacturing program for aftermarket services. Our policies exploit the ability to leverage OE production to support both the OE service operations as well as demand from the IAM. To the best of our knowledge, this research is the first attempt of its kind in the remanufacturing literature, as prior research treated these interrelated decisions separately. Valuable managerial insights are obtained by minimizing the discounted cash outflows caused by appropriate investment and core return inventory building decisions. We show that, under certain conditions, it may be optimal to delay the launch of the remanufacturing program to build up an adequate initial core return inventory. This may help in perfectly substituting virgin parts with remanufactured parts after end of the OE production run. At operational level, efficient production planning and control of reman parts for the supplier heavily impinges on the ability to accurately forecast core returns from customers (e.g., dealers, distributors). There are several challenges to this, including, the volume and diversity of customers served by the supplier, differences among individual customer warehouses in returning cores, large reman product catalogs, changing customer behaviors (often improving core return delays), and data sparsity. In this research we report the evidence for the effectiveness of hazard rate regression models to estimate core return delays in the context of remanufacturing. We investigate a number of hazard rate modelling techniques (e.g., parametric, semi-parametric etc.) using real-world datasets from a leading Tier-1 automotive supplier. Results indicate the effectiveness of the proposed framework in terms of stability and face validity of the estimates and in predictive accuracy

A Framework for Reverse Logistics

Reverse Logistics has been stretching out worldwide, involving all the layers of supply chains in various industry sectors. While some actors in the chain have been forced to take products back, others have pro-actively done so, attracted by the value in used products One way or the other, Reverse Logistics has become a key competence in modern supply chains. In this paper, we present a content analysis of reverse logistics issues. To do so, we propose a content framework focusing on the following questions with respect to reverse logistics: why? what? how?; and, who?, i.e. driving forces and return reasons, what type of products are streaming back, how are they being recovered, and who is executing and managing the various operations. These four basic characteristics are interrelated and their combination determines to a large extent the type of issues arising from the resulting reverse logistics system.supply chain management;reverse logistics;content analysis;theory;framework

Improving Demand and Supply Balance in a Closed-Loop Supply Chain : A Case Study in a Dynamic Reuse Spare Part Business

Many companies have adopted closed-loop supply chain (CLSC) systems in pursuit of greener operations through reuse product offering. Contrary to traditional forward supply chains, CLSCs combine both supply chain directions, forward and reverse. As well, the CLSC incorpo-rates circular manufacturing process into the loop, such as repairing, refurbishing, or reman-ufacturing. The combination of multiple simultaneous processes leads to added complexity in a circular system. This results in a wide range of challenges faced by a CLSC. The CLSC pro-cess challenges present themselves as unbalanced demand for reuse products and supply for returning end-of-use cores. As a result, this study’s purpose was to identify the most critical challenges contributing to an unbalanced demand and supply. Also, the study aimed to pro-vide improvement proposals to improve the situation at the case company. To realise this purpose, the study followed the format of a qualitative case study with a maritime company Wärtsilä as the case company. The research data was collected using open interviews with eight key stakeholders involved in the case company’s CLSC. Data from the interviews was then transcribed and analysed with a thematic analysis method; categorising found challeng-es into challenge categories identified from the existing literature. To examine the most criti-cal CLSC challenges, the study performed a criticality analysis using Process Failure Mode & Effect Analysis (PFMEA). PFMEA assigned severity to each found challenge while also evaluat-ing the case company’s current methods for prevention and detection. The analysis resulted in 14 different challenge categories expected to contribute to unbalanced demand and sup-ply. Two new challenge categories, challenges with process knowledge and challenges with a missing seeding strategy, were added to the body of knowledge. Regarding criticality, seven challenge categories were found as critical. Critical challenges in reverse supply chain pro-cesses related to limited internal and external process knowledge and visibility of returning cores. Critical challenges in circular manufacturing processes related to low core availability, pull-ordering system, outdated inventory management practices, and a missing seeding strategy. Finally, the study proposed improvement proposals for the critical challenges that would result in more balanced demand and supply. These findings stress the individual needs of each CLSC system to perform in an optimal manner. The case company’s single source for cores created new challenges that were yet to be identified by the existing litera-ture. Also, the separation of critical challenges aids managers in focusing on the most critical ones in often problem-rich CLSCs

Forecasting return of used products for remanufacturing using graphical evaluation and review technique (GERT)

This research develops a forecasting model that can predict the quantity, time and probability of product return, recyclable parts/components/materials and disposal. It adopts the Graphical Evaluation and Review Technique (GERT) by translating the remanufacturing operational process into a stochastic network. This stochastic network possesses two characteristics: activities having a probability of occurrence associated with them; and time to perform an activity. Together with the GERT method, Mason’s rule is applied to calculate the equivalence transfer function of the system, therefore predicting the desired outcomes. A generic eight-step process on how to implement this method in any structure of return products and remanufacturing network is provided. A numerical example is presented to demonstrate the result of using GERT on forecasting printer remanufacturing outcomes. The main contribution of this research is: Instead of giving one result such as either return quantity, or time, or probability, our research can forecast three of these outcomes simultaneously, and the algorithm is generalised to be applicable to any product structure and remanufacturing network

A Conceptual Framework of Reverse Logistics Impact on Firm Performance

This study aims to examine the reverse logistics factors that impact upon firm performance. We review reverse logistics factors under three research streams: (a) resource-based view of the firm, including: Firm strategy, Operations management, and Customer loyalty (b) relational theory, including: Supply chain efficiency, Supply chain collaboration, and institutional theory, including: Government support and Cultural alignment. We measured firm performance with 5 measures: profitability, cost, innovativeness, perceived competitive advantage, and perceived customer satisfaction. We discuss implications for research, policy and practice

Forecasting of Core Returns for Remanufacture: A Time Series Analysis

Over centuries, consumption of natural resources has been on a steady increase in re-sponse to the increasing global population. Increased and unsustainable use of natural re-sources in addition to increased manufacturing is a ecting the environment adversely. Hence, governments and environmental protection agencies are implementing rm regulations for industries to reduce their footprint on environmental pollution, for instance by ensuring that their waste products are not only disposed sustainably but also reduced. In response to these regulations, industries have embraced product end-of-life management strategies. These include reverse logistic, material and product recovery, reusing, recyling and remanufacturing. This Thesis addresses one of the major challenges in remanufacturing which is uncertain-ties in the number of core returns for remanufacture. Speci cally, we propose a time series model that uses real data from a partner International OEM company that manufactures aswell as remanufactures electronic products. A unique aspect of the data that was obtained was the fact that speci c distinctions were made delineating billable return products from warranty return products for remanufacture. It is with this uniqueness that we sort to con-struct three time series model that is (a) Overall product core return; (b) Warranty return and (c) Billable return. The forecast for the overall product core return and billable return was calculated using the Seasonal ARIMA (autoregressive integrated moving average) model, whereas the war-ranty return forecast was calulated using the ARIMA model. The best model was selected on the basis of akaike information criterion. ARIMA(0,1,1)(0,1,0)[12] was selected as the best model for overall returns; ARIMA(0,1,1) was selected as the best model for warranty return and ARIMA(0,1,0)(0,1,0)[12] was selected as the best model for billable return. The se-lected models were proven to be appropriate by means of residual diagnostics which includes Box-Ljung test, residuals of ACF, ARCH e ect and Jarque Bera test. Two-thirds of the data was used to build the models. After veri cation, this models were used to forecast the remaining one-third of the data. The accuracy of these forecasting results were determined with ME, RMSE, MAE, MPE, MAPE, MASE and ACF1. Overall, though not generizable to all companies, our model proved that for our partner company the overall returns were largely driven by the billable returns hence making it a pro table venture

Integrating Closed-loop Supply Chains and Spare Parts Management at IBM

Ever more companies are recognizing the benefits of closed-loop supplychains that integrate product returns into business operations. IBMhas been among the pioneers seeking to unlock the value dormant inthese resources. We report on a project exploiting product returns asa source of spare parts. Key decisions include the choice of recoveryopportunities to use, the channel design, and the coordination ofalternative supply sources. We developed an analytic inventory controlmodel and a simulation model to address these issues. Our results showthat procurement cost savings largely outweigh reverse logistics costsand that information management is key to an efficient solution. Ourrecommendations provide a basis for significantly expanding the usageof the novel parts supply source, which allows for cutting procurementcosts.supply chain management;reverse logistics;product recovery;inventory management;service management