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The purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry factors which have an effect on these characteristics so as to improve these factors.

Grey system theory has prominent advantage of using few data and uncertainty information to analyze many factors. Therefore, it is more suited for system analysis than traditional statistical analysis methods like regression analysis, variance analysis and principal component analysis, which require massive data, certain probability distribution in the data and few variant factors. So in this paper, grey incidence analysis method, which is an important part of grey system theory, is used to identify industry characteristics and key industry factor of remanufacturing industry in China and then put forward appropriate industrial policies and countermeasures to improve these industry factors.

According to the results of this study, it reveals that there are no most favorable industry characteristics and no most favorable industry factors in remanufacturing industry of China. “Annual sale of remanufacturing industry” is identified as quasi-preferred industry characteristic, and “total number of employees with master degree or above in remanufacturing enterprise” is identified as the quasi-preferred industry factor. “Total building area of remanufacturing enterprise” is referred as the most unfavorable industry factors.

Judging from the findings of this study, four practical implications are summarized as follows: “annual sale of remanufacturing industry” should be given great importance because it is a quasi-preferred industry characteristic. “Total number of employees with master degree or above in remanufacturing enterprise” and “total number of research institution and university participated in remanufacturing” should be further strengthened by establishing an industry-university-research institute collaboration network, due to the fact that they are the top two quasi-preferred industry factors. “Total investment of remanufacturing industry” and “total annual R&D expenditures” have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. “Total building area of remanufacturing enterprise” must be strictly controlled because of its little impact on remanufacturing industry.

In this research, grey incidence analysis is applied to identify key industry factors of remanufacturing industry for the first time. It helps in finding industry factors which are in urgent need of improvement and assists in making appropriate industrial policies and countermeasures to improve them by studying relationships between industry characteristic and industry factors.

Although China can be considered an early adopter of the circular economy, there are few studies of remanufacturing business models (BMs) in the context of the Chinese automobile industry. The purpose of this paper is to investigate viable BMs, summarizes current obstacles and anticipates future development opportunities and directions.

The cross-case analysis considers the roles of value networks and of customer value proposition and interface in circular business models (CBMs) by examining the strategies and tactical measures of two leading remanufacturers. The data are collected from semi-structured interviews, documents, etc.

The analysis identifies the following components of viable BMs of remanufacturers: reclaiming raw material, managing used components, producing new products and marketing. Several current obstacles are summarized from four perspectives: policy barriers and insufficient government support; consumer awareness; related product quality; and technology. The study also identifies future directions and opportunities for the automobile parts remanufacturing industry.

This study contributes to the CBM literature by mapping the barriers and opportunities in remanufacturing. The results have shed some light into the field of sustainability in manufacturing firms by empirically testing the theoretical model. The results will help managers to design viable CBMs in different contexts.

This paper designs an optimal closed-loop supply chain network with an integrated forward and reverse logistics to examine the possibility of remanufacturing end-of-life (EoL) ships.

Explanatory variables are used to estimate the number of EoL ships available in a closed-loop supply chain network. The estimated number of EoL ships is used as an input in the model and then it is solved by a mixed-integer linear programming (MILP) model of the closed-loop supply chain network to minimise the total logistic costs. A discounted payback period formula is developed to calculate the length of time to recoup an investment based on the investment's discounted cash flows. Existing ship wrecking industry clusters in the Western region of India are used as the case study to apply the proposed model.

The MILP model has optimised the total logistics costs of the closed-loop supply network and ascertained the optimal number and location of remanufacturing for building EoL ships. The capital and variable costs required for establishing and operating remanufacturing centres are computed. To remanufacture 30 ships a year, the discounted payback period of this project is estimated to be less than two years.

Ship manufacturing businesses are yet to re-manufacture EoL ships, given high upfront capital expenditure and operational challenges. This study provides management insights into the costs and benefits of EoL ship remanufacturing; thus, informing the decision-makers to make strategic operational decisions.

The design of an optimal close loop supply chain network coupled with a Bayesian network approach and discounted payback period formula for the collection and remanufacturing of EoL ships provides a new integrated perspective to ship manufacturing.

To provide in‐depth insights into one specific product recovery operation (remanufacturing) in the automotive sector, taking the example of original equipment manufacturers (OEM).

The research was undertaken within the engine remanufacturing facilities of a major European car manufacturer. The main data collection methods were open‐ended, non‐directive interviews and process observation. In addition, secondary data (internal company reports and documentation) were collected. Overall, a total of 64 interviews were conducted within the engine remanufacturing plant.

The case study revealed that the remanufacturing processes included challenges that have been traditionally investigated within “conventional” operations and supply chain management, such as high inventory levels or process through‐put times. It was also found that product take‐back and recovery in the automotive sector do not necessarily stem from a company's mission statement that includes (sustainable) responsibility, but are based on other motives. These motivations include the long‐term supply of spare parts, for example.

The findings are limited to one specific European car manufacturer and may therefore not necessarily apply to the independent automotive remanufacturing sector or to other OEM remanufacturers.

The case study gives an in‐depth insight into the issues within automotive product take‐back and recovery, the types of obstacles that may occur as well as how these may be overcome in the real world.

The findings provide new, real‐world insights for academia, but also feedback to industry by providing an in‐depth account of current automotive remanufacturing practices undertaken by the OEM.

The optimal control on reassembly (remanufacturing assembly) error is one of the key technologies to guarantee the assembly precision of remanufactured product. However, because of the uncertainty existing in remanufactured parts, it is difficult to control assembly error during reassembly process. Based on the state space model, this paper aims to propose the optimal control method on reassembly precision to solve this problem.

Initially, to ensure the assembly precision of a remanufactured car engine, this paper puts forward an optimal control method on assembly precision for a remanufactured car engine based on the state space model. This method takes assembly workstation operation and remanufactured part attribute as the input vector reassembly status as the state vector and assembly precision as the output vector. Then, the compensation function of reassembly workstation operation input vector is calculated to direct the optimization of the reassembly process. Finally, a case study of a certain remanufactured car engine crankshaft is constructed to verify the feasibility and effectiveness of the method proposed.

The optimal control method on reassembly precision is an effective technology in improving the quality of the remanufactured crankshaft. The average qualified rate of the remanufactured crankshaft increased from 83.05 to 90.97 per cent as shown in the case study.

The optimal control method on the reassembly precision based on the state space model is available to control the assembly precision, thus enhancing the core competitiveness of the remanufacturing enterprises.

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.

Remanufacturing is a process whereby value from old products is recovered by replacing and recovering used components to bring such products to a new or like-new state. Today, both original equipment manufacturers (OEMs) and third parties are engaged in remanufacturing activities, investing in many locations throughout Asia. The purpose of this paper is to examine the reasons for initiating remanufacturing activities as well as the location determinants for the remanufacturing sector in Asia.

The authors conduct a multiple case study. Triangulation is applied to gain objective views from interviewing three OEMs, one logistics firm, and three local small enterprises. Real options theory is the theoretical lens used to examine the location choice of the OEMs.

Firms engaged in remanufacturing tend to co-locate facilities with existing manufacturing facilities, and those investing in new sites for remanufacturing view the regulatory environment as the most important factor. OEMs tend to leverage on existing manufacturing facilities or third-party remanufacturers to reduce their cost of commitment when starting remanufacturing at new locations.

The sample size is still small for the generalization of the results. Further empirical study is needed to test the propositions from this paper.

This paper could assist managers and decision makers in the multinational corporations to design appropriate logistics-related solutions for remanufacturing in Asia.

The authors work contributes to the theory on remanufacturing location determinants. It shows that OEMs and third-party remanufacturers can have a collaborative relationship instead of the commonly assumed competitive one, which is currently not found in the literature.

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 study was to research how the reassembly (remanufacturing assembly) achieves a quality that is not lower than original production with different precision remanufactured parts based on the integration of mechanics, mathematics (measurement uncertainty) and management (optional classification). Remanufactured product quality is the soul of the remanufacturing project.

First, this paper studies the recycled parts features and reassembly features. Then, we build the mathematical sub-model with remanufactured parts and dimensional precision, which is proven that optional classification can effectively improve the reassembly accuracy mathematically. The optimization model of optional classification for reassembly is proposed under the constraint of a dimensional chain, and the solutions are studied based on particle swarm optimization. Finally, this method is applied in a remanufacturing enterprise and achieves good results.

The method can reduce the cost of quality loss and improve the quality of remanufactured products.

It provides a new solution and idea for reassembly with different precision remanufactured parts and promotes the healthy development of reverse logistics with a high level of customer satisfaction. This method can maximize the use of different levels of quality remanufactured parts and improve reassembly accuracy by mathematical proofs and examples.

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.