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With the improvement of economic level, car ownership is growing, and the number of scrapped automobiles is increasing. Therefore, evaluation research for auto parts remanufacturing is particularly important. The purpose of this paper is to construct the evaluation index system of auto parts remanufacturing and research the grey clustering theory. The grey fixed weight clustering evaluation is used to evaluate automobile engine remanufacturability.

According to the policies and regulations of China about remanufacturing, economic, technical, resources, energy and the environment, four indexes are selected to set up the evaluation standard of auto parts remanufacturing scheme. Grey fixed weight clustering method is used to evaluate remanufacturability of the auto parts. Firstly, number index and grey determine the whitenization weight function, then based on the clustering weight of each index, the clustering coefficient matrix is calculated. Finally, the class that certain object belongs to, according to the clustering coefficient matrix is determined.

Results show that constructed indexes of auto parts remanufacturing scheme can be used for effective evaluation. And the proposed fixed weight grey cluster model can aggregate all indexes information well. Therefore, the proposed indexes and model in this paper are effective and can be used for auto parts remanufacturing.

According to the requirements of the current situation in China, this paper puts forward a method based on grey clustering decision, to evaluate different auto parts remanufacturing schemes, for manufacturing enterprises to provide theoretical basis for remanufacturing production, in order to realize the reasonable configuration of resources.

This paper firstly establishes the evaluation index system of auto parts remanufacturing, the grey clustering theory is introduced into the evaluation of remanufacturing. The fixed-weight grey cluster model is proposed to aggregate indexes’ information.

The study investigated the effect of big data analytics capabilities (BDACs) on reverse logistics (strategic and tactical) decisions and finally on remanufacturing performance.

The primary data were collected using a structured questionnaire and an online survey sent to South African manufacturing companies. The data were analysed using partial least squares based structural equation modelling (PLS–SEM) based WarpPLS 6.0 software.

The results indicate that data generation capabilities (DGCs) have a strong association with strategic reverse logistics decisions (SRLDs). Data integration and management capabilities (DIMCs) show a positive relationship with tactical reverse logistics decisions (TRLDs). Advanced analytics capabilities (AACs), data visualisation capabilities (DVCs) and data-driven culture (DDC) show a positive association with both SRLDs and TRLDs. SRLDs and TRLDs were found to have a positive link with remanufacturing performance.

The theoretical guided results can help managers to understand the value of big data analytics (BDA) in making better quality judgement of reverse logistics and enhance remanufacturing processes for achieving sustainability.

This research explored the relationship between BDA, reverse logistics decisions and remanufacturing performance. The study was practice oriented, and according to the authors’ knowledge, it is the first study to be conducted in the South African context.

In a quest to meet increasing pressure to incorporate environmental and sustainability factors due to the legislations and growing public awareness, companies are rethinking of strategizing their supply chain network to take control of the reverse flow of products as well. This growing interest has also led to tremendous growth in publications occurring in several reputed journals in the last few years. In this context, the purpose of this article is to perform a systematic literature survey of recent and state-of-the-art papers in order to draw insights and highlight the future directions.

This paper has selected and reviewed 204 papers published from the year 2002–2017. The papers were collected from the web of science and Google scholar database which have the DOI number. The selected papers were then categorized into main five core areas of RSC management namely reverse supply chain (RSC), Reverse Logistics (RL), Remanufacturing, Closed-Loop Supply Chain (CLSC) and Product Recovery Systems (PRS) and then analyzed with great detail. Finally, the research gaps that were identified from the study have been highlighted for future research opportunities.

This paper would serve as a roadmap to the managers who wish to align their forward and reverse supply chains for overall growth and development. It provides an in-depth knowledge on RSC to the researchers working in this domain. The scholars would be able to identify the areas of RSC which have been already addressed and the areas which remain unaddressed.

This paper presents a systematic literature survey of state-of-the-art papers that was published in the reputed journal in the area of RSC. Total 204 numbers of papers which were published in the reputed journals between 2002 and 2017 are reviewed, categorized and analysed to draw the opportunities and future research direction in the area of RSC.

This research aims to propose a methodology for a systematic, concurrent consideration of design for assembly (DFA) and disassembly guidelines and constraints for product remanufacturing. The methodology provides a holistic approach to design product from the remanufacturing perspective.

The proposed methodology incorporates parts’ integration assessment and evaluation of part complexity and accessibility taking into consideration both DFA and design-for-disassembly (DFD) guidelines and constraints. Metrics for accessibility and complexity in retrieving the remanufacturable cores from a product are evaluated to determine the best possible disassembly route considering the practical constraints which an operator might face during disassembly. As there could be more than one feasible disassembly route to retrieve a core during remanufacturing, a disassembly evaluation is conducted to determine the optimal path after combination of the parts of the assembly.

In remanufacturing, products need to be disassembled and re-assembled again. Conflicts exist between DFA and DFD. The proposed methodology serves to address these conflicting issues. The proposed methodology eases a designer’s effort systematically to incorporate both aspects, by incorporating practical consideration to determine an optimal disassembly sequence through integrating the handling aspect of assembly complexity assessment with the U-Rating disassembly effort indexing scheme to provide a quantitative evaluation of disassembly complexity, as disassembly still largely requires human effort.

Future research will explore methods to improve the user interface with features to determine feasible disassembly routes of a product automatically. This will relieve the effort of the product designer to a great extent.

This paper proposes a methodology for a systematic, concurrent consideration of DFA and DFD to provide a holistic approach to product design from the remanufacturing perspective to ease the designer’s task. Practical considerations will be made to determine the optimal disassembly route of the product. DFD will only be required to be applied to the selected disassembly route to minimize conflicts with DFA.

Re-use of products in the supply chain has become a significant consideration in the last decade. It has resulted in the development of several product recovery alternatives. Remanufacturing in the supply chain is one such product recovery option that yields social, economic and environmental benefits. This study aims is to identify and evaluate the key performance indicators (KPIs) of the remanufacturing supply chain (RSC).

The KPIs of RSC are classified along with the five primary management processes (plan, source, make, deliver and return) of the supply chain operations reference (SCOR) model. A grey decision-making trial and evaluation laboratory (DEMATEL) technique is applied to investigate the complex interrelationships amongst the identified KPIs and categorize them into cause and effect group. The applicability of the proposed framework is demonstrated through a case organization involved in remanufacturing business.

The KPIs are identified based on literature analysis and subsequent discussion with decision panel experts. The present research work results reveal that “consumer awareness program”, “technological compatibility” and skilled workforce' are the most influential indicators.

This research work provides a framework to evaluate the causal relationship between the RSC KPIs. The framework proposed in this study is empirically applied to a case organization. Based on the study findings some important recommendations are presented to the decision-makers/policy planners to help them develop an action plan. This would help the case organization reduce resource consumption, increase market share and enable sustainable development.

The purpose of this study is to present a system dynamic (SD)-based remanufacturing economic analysis model of used automobile engine under two recycling modes. The authors will compare the remanufacturing cost, sales profit and sales revenue from time and space dimensions incurred in different recycling modes in the long run.

The remanufacturing economic analysis model is based on SD methodology. The authors can simulate the relations of impact factors on automobile engine recycling and remanufacturing and further analyze and compare the cost, sales profit and sales revenue incurred in different recycling modes in the long term.

Sinotruk Steyr engine remanufacturing in Shandong province is taken as the research case subject. The revenue, cost and profit under the two recycling modes from 2015 to 2035 are analyzed and compared. The results show that different recycling modes have significant varying influence on the economy of engine remanufacturing.

This economic analysis model can provide a method reference to decide the recycling mode for auto components and other product remanufacturing. Moreover, this model can guide and support the sustainable development of remanufacturing industry.

This paper examines how the level of low-carbon awareness (LCA) affects the remanufacturing strategy in a supply chain with an original equipment manufacturer (OEM) and an independent remanufacturer (IR) competing with each other.

Game theory and operations optimization.

The studies analytically characterize the threshold levels of the LCA in response to which the OEM and the IR will change their remanufacturing strategies from no remanufacturing to partial remanufacturing and then to full remanufacturing. In addition, the studies reveal that as compared with the OEM, the IR has more flexibility in terms of the market entry to remanufacturing with the level of LCA increasing. With the extended studies, it is exhibited that the above findings are robust to a good extent.

It can provide decision support for remanufacturing enterprises.

There is now much emphasis in both research and practice on the principles of circular economies. In this paper remanufacturing is examined as a key enabler of circular practices, and the concept of “Product-Agnostic Manufacturing” (PAR) is proposed. This work differentiates PAR from many traditional approaches to remanufacturing by virtue of PAR's treatment of product variety. Most existing approaches to remanufacturing feature low variety and standardisation; this study instead suggests that the exploitation of flexibilities in both operations and supply chains leads to new competitive strategies for firms to exploit.

This is a conceptual study that builds on a thorough exploration of contemporary remanufacturing literature in the development of the new PAR concept.

Through a detailed literature review it is shown that there are a range of benefits, challenges, and critical success factors that underpin the remanufacturing concept. Building on this understanding and bridging literature in operations flexibility and supply chain design, a detailed discussion on the nature of PAR is provided, and an agenda for future research developed.

Whilst there has been much literature on remanufacturing, there is a general tendency to treat supply chain and remanufacturing operations quite distinctly in individual articles. Additionally, there has been little consideration of multi-product remanufacturing, and for the limited studies where this is done, the emphasis is typically on problem avoidance. This study aims to provide a detailed insight into the developed PAR concept, showing how the remanufacture of a wide range of product varieties may be achieved through flexible operations and supply chain design.

The purpose of this paper is to investigate the optimal production and financing strategies for the closed-loop supply chain (CLSC) composed of a capital-constrained original equipment manufacturer (OEM) and a risk-averse authorized remanufacturer (RM).

The authors formulate four models with different scenarios, namely, the OEM has sufficient capital; the OEM has limited capital without financing; the OEM adopts debt financing strategy; and the OEM adopts equity financing strategy. The equilibrium solutions of each scenario are obtained by backward induction method, the influences of risk aversion coefficient on the equilibrium solutions are examined and the OEM's optimal financing strategy is found by comparison analysis.

When the OEM's initial capital is limited and the equity dividend ratio is less than a certain threshold, the equity financing strategy is more advantageous for the OEM. However, if the OEM's initial capital is extremely scarce and the dividend proportion is large, the OEM prefers the debt financing strategy. When considering financing, consumer surplus always decreases as the risk aversion factor increases; the debt financing strategy is more environmentally friendly compared with the equity financing strategy. Only the debt financing strategy can make both members in the CLSC achieve a win-win situation in a certain region when the dividend ratio is sufficiently large.

It will be more fascinating if the model extends to such a case that the production operation situation in the CLSC composed of multiple OEMs in multiple periods. Furthermore, the remanufacturer's risk-averse information is asymmetry may be more realistic in our daily life.

There are three main differences from the existing research. One is that the remanufacturer's risk aversion originates from the uncertain remanufacturing cost instead of the uncertain market demand. Another is that the boundary conditions of the OEM prefer to adopt debt financing is obtained through the envelope theorem with Lagrange multiplier method. Last but not the least, this paper provides a good theoretical reference and practical guidance for the OEM to make the rational financing strategy selection in face of different degree of capital scarcity in the CLSC system. The value of the three aspects provides a theoretical basis for the optimal operation decisions of capital-constrained manufacturer considering the remanufacturer's risk aversion in the CLSC operation system.

The uncertainty of remanufacturing parts is a key factor affecting the quality of remanufactured products. Therefore, the purpose of this paper is to measure the uncertainty of remanufactured parts and study the coupling mechanism of reassembly quality.

First, uncertainty of remanufactured parts is analyzed, and the uncertainty measure model for remanufacturing parts based on entropy is constructed. Second, the nonlinear mapping model between the uncertainty and reassembly quality were studied using Gauss-Newton iterative method to reveal the coupling mechanism between uncertainty of remanufacturing parts and reassembly quality. Finally, the model is verified in the reassembly process of remanufacturing cylinder head.

The method can guide reassembly operations to improve the reassembly quality with uncertainty of remanufactured parts.

This study provides practical implications by developing a multivariate nonlinear mapping model for reassembly quality based on entropy to determine the uncertainty factors that affect the reassembly quality significantly and then correct the reassembly operation to better optimize the allocation of remanufacturing production resources. The study also theoretically contributes to reveal the coupling mechanism of reassembly quality with the uncertainty of remanufactured parts.