A systematic review of decision-making in remanufacturing

Potential benefits have made remanufacturing attractive over the last decade. Nevertheless, the complexity and uncertainties associated with the process of managing returned products make remanufacturing challenging. Since this process involves enormous decision-making practices, various methods/techniques have been developed. This review is to specify the current challenges and opportunities for decision-making in remanufacturing. To achieve this, we perform a systematic review over decision-making in remanufacturing by classifying decisions into different managerial levels and areas. Adopting a systematic approach which provides a repeatable, transparent and scientific process, 241 key articles have been identified following a multi-stage review process. Our review indicates that most studies focuses on strategic-level(48%) and tactical-level (34%)with only 5% focusing on operational-level and the rest on two levels(13%). Regarding decision-making methods, most studies propose mathematical models (60%) followed by analytical models (31%). Furthermore, only 36% of the studies address uncertainties in which stochastic approach is mostly applied. A total of 21 knowledge gaps are highlighted to direct future research work

Modeling a Remanufacturing Reverse Logistics Planning Problem: Some Insights into Disruptive Technology Adoption

Remanufacturing is the process to restore the functionality of high-value end-of-life (EOL) products, which is considered a substantial link in reverse logistics systems for value recovery. However, due to the uncertainty of the reverse material fow, the planning of a remanufacturing reverse logistics system is complex. Furthermore, the increasing adoption of disruptive technologies in Industry 4.0/5.0, e.g., the Internet of things (IoT), smart robots, cloud-based digital twins, and additive manufacturing, has shown great potential for a smart paradigm transition of remanufacturing reverse logistics operations. In this paper, a new mixed-integer program is modeled for supporting several tactical decisions in remanufacturing reverse logistics, i.e., remanufacturing setups, production planning and inventory levels, core acquisition and transportation, and remanufacturing line balancing and utilization. The model is further extended by incorporating utilization-dependent nonlinear idle time cost constraints and stochastic takt time to accommodate diferent real-world scenarios. Through a set of numerical experiments, the infuences of diferent demand patterns and idle time constraints are revealed. The potential impacts of disruptive technology adoption in remanufacturing reverse logistics are also discussed from managerial perspectives, which may help remanufacturing companies with a smart and smooth transition in the Industry 4.0/5.0 era

Warranty and Maintainability Analysis for Sensor Embedded Remanufactured Products in Reverse Supply Chain Environment

Remanufactured products are very popular with consumers due to their appeal to offer the latest technology with lower prices compared to brand new products. The quality of a remanufactured product induces hesitation for many consumers, in regards to its efficacy and reliability. One stratagem that remanufacturers could employ to encourage customer security are product warranties. This paper studies and scrutinizes the impact that would be had by offering renewing warranties on remanufactured products. This study was able to determine the optimal costs of warranty for two-dimensional non-renewable warranty offered on remanufactured products using the simulation model and design of experiments

Pricing and warranty decisions in a two-period closed loop supply chain

For a two-period closed loop supply chain (CLSC) consisting of a manufacturer and a retailer, Stackelberg game analyses are conducted to examine pricing and warranty decisions under two warranty models depending on who offers warranty for new and remanufactured products and the corresponding benchmark models with warranty for new products only. Next, we identify the conditions under which warranty for remanufactured products is offered and investigate how this warranty affects the CLSC operations. Subsequently, comparative studies are carried out to examine equilibrium decisions, profitability and consumer surplus of the CLSC between the two warranty models. Analytical results show that offering warranty for remanufactured products does not affect new product pricing in period 2, but influences pricing of new products in period 1 and remanufactured products in period 2, thereby enhancing remanufacturing, individual and channel profitability, and consumer surplus. Compared to the retailer warranty for remanufactured products, the manufacturer warranty can attain a more equitable profit distribution. If the warranty cost advantage of the manufacturer (retailer) is significant relative to that of the retailer (the manufacturer), the manufacturer (retailer) arises as a natural choice to offer warranty for remanufactured products as this decision enhances both profitability and consumer surplus

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

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

CANON: A Circular Economy Business Model Case

This report presents the case study of Canon’s EMEA business for Document Solutions (DS), with a focus on the business model for remanufacturing and refurbishment. It was chosen as it provided an example of a mature remanufacturing model, as well as potential for further circularity and business benefit through expansion of refurbishment activities. Canon EMEA has also been growing services such as Managed Print Service (MPS) – a service-based model for providing printer copiers – which, while not a focus of the case study, provides opportunities for both remanufacturing and refurbishment. Canon operates in a market which is currently in decline, with vendors competing intensely for market share. This is creating a stark contrast between a business model driven by new product sales, and one that emphasises the cultivation and reutilisation of existing deployed assets. In this context, it is important to emphasise that this case study focuses on the circular business models and potential for Canon EMEA, whose business is principally a combination of sales/marketing and service delivery. This is in contrast to Canon Inc. (Japan) who manufactures and supplies equipment for Canon EMEA to sell and integrate into its service offerings. This case study explores the opportunities, as well as enablers and barriers, to Canon expanding the role of remanufacturing and refurbishment within its circular business models. We believe this will have important positive implications for Canon given the broader strategic challenges it face