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Aims to develop a selective disassembly methodology for generating an optimum disassembly sequence for end‐of‐life (EOL) products.

The paper presents a selective disassembly methodology for EOL products. In order to achieve this, Nevins and Whitney's methodology for assembly was modified. In addition, a Java‐based software was developed to speed up the generation of all possible disassembly sequences.

Finds that the methodology developed by Nevins and Whitney for assembly is applicable to disassembly process. In addition, the winnowing process for disassembly is much easier than for assembly because of the selective disassembly approach, which automatically provides a significant constraint on possible sequences.

Provides an easy to use and visual disassembly sequence generation tool for end‐of‐life products.

Disassembly is one of the significant cost drivers in achieving close loop manufacturing. Application of the methodology proposed in this paper will significantly reduce the disassembly time by providing a disassembly sequence for the selected components with reuse potential.

Provides a graphical representation of disassembly sequences at different stages of the process, which allows the user to visualize the disassembly process.

To improve the efficiency of end-of-life product’s disassembly process, this paper aims to propose a disassembly sequence planning (DSP) method to reduce additional efforts of removing parts when considering the changes of disassembly directions and tools.

The methodology has three parts. First, a disassembly hybrid graph model (DHGM) was adopted to represent disassembly operations and their precedence relations. After representing the problem as DHGM, a new integer programming model was suggested for the objective of minimizing the total disassembly time. The objective takes into account several criteria such as disassembly tools change and the change of disassembly directions. Finally, a novel hybrid approach with a chaotic mapping-based hybrid algorithm of artificial fish swarm algorithm (AFSA) and genetic algorithm (GA) was developed to find an optimal or near-optimal disassembly sequence.

Numerical experiment with case study on end-of-life product disassembly planning has been carried out to demonstrate the effectiveness of the designed criteria and the results exhibited that the developed algorithm performs better than other relevant algorithms.

More complex case studies for DSP problems will be introduced. The performance of the CAAFG algorithm can be enhanced by improving the design of AFSA and GA by combining them with other search techniques.

DSP of an internal gear hydraulic pump is analyzed to investigate the accuracy and efficiency of the proposed method.

This paper proposes a novel CAAFG algorithm for solving DSP problems. The implemented tool generates a feasible optimal solution and the considered criteria can help the planer obtain satisfactory results.

This paper aims to develop methods for generating disassembly tasks for selective disassembly. The disassembly task contains the disassembly information, namely, disassembly direction, disassembly tool and selective disassembly sequence.

Ontology is adopted to represent the product, and ontology rules are used to represent the disassembly knowledge. A product ontology model (POM) is introduced on the basis of material, connection matrix and interference matrix. Two types of disassembly knowledge are taken into account, one is the disassembly knowledge of disassembly tool selection and the other is the disassembly knowledge of special connections. Based on the POM and the disassembly knowledge, decision support methods are designed to generate disassembly tasks.

A centrifugal pump is used to demonstrate the proposed methods, and the result shows that the methods work well.

The methods developed in this study are fundamental approaches. The ontology and the ontology rules can be extended with more disassembly knowledge.

The main contribution of this research is the development of methods for representing disassembly knowledge based on ontology rules and the decision support methods for generating disassembly tasks.

To improve the efficiency and economy of electro-mechanical product's recycle process, this paper aims to propose a disassembly sequence planning (DSP) method to reduce additional efforts of removing extra parts in selectable disassembly.

The methodology has three parts, which includes a disassembly hybrid graphic model to describe the product disassembly information, an object inverse-directed method to optimize the disassembly design and a model reconstruction method to achieve a better DSP.

According to the disassembly cost criteria and the parameters of disassembly tools, the disassembly efficiency increases and the disassembly cost decreases due to the use of partial destructive mode compared with non-destructive mode. The proposed partial destructive DSP is more efficient and economical.

Partial destructive disassembly mode cannot be used for the flammable or explosive component in the procedure of the DSP optimization algorithm.

DSP of an electric corkscrew is analyzed to investigate the accuracy and efficiency of the proposed method.

This paper proposes a partial destructive disassembly based DSP method for product disassembly, which provides a new approach for the disposal of end-of-life products.

The purpose of this paper is to report on research undertaken to investigate whether current reverse logistics theories and models can be totally applied in developing countries like China using the electronic industry as a case study.

A case study approach was adopted with information collected from company web sites, direct observation, and in‐depth interviews with four major consumer electronic product manufacturers in China. Findings were analyzed and compared across all the cases studied to determine the common external and internal drivers for reverse logistics implementation as well as the obstacles faced by the whole electronic industry. A comparison with the literature was made to identify the gaps between current theories and models and actual practices in China.

The findings suggest that while reverse logistics drivers vary from company to company, barriers to reverse logistics are common and are mainly external. The major difficulty in implementing reverse logistics in the electronic industry of China is the lack of enforceable laws, regulations or directives to motivate manufacturers. Furthermore, economic support and preferential tax policies are absent to help manufacturers offset the high investment costs of reverse logistics. Low public awareness of environmental protection and underdevelopment of recycling technologies are also some of the obstacles to widespread reverse logistics implementation. The findings also reveal the presence of linkages between the various external factors that are not fully explored in current reverse logistics models.

The study corroborates the application of transaction cost economics and resource‐based view theory to account for the different approaches to reverse logistics adopted by firms in developing countries. It also reveals a need for further research on the linkages between external factors affecting reverse logistics implementation. The four case studies of large corporations are drawn from a Chinese setting in which implementation of reverse logistics is still in an early stage. The complex nature of China's transitional economy and political considerations may influence the perspectives and practices of small manufacturers in the management of environmental issues thus limiting the generalizability of the findings.

The study reveals the problems encountered in the implementation of reverse logistics in China and proposes measures to expedite the development.

This paper presents a systematic analysis of the external and the internal factors affecting reverse logistics implementation in developing countries like China. It reveals the need to investigate the linkages between the various external factors that are less explored in current reverse logistic theories and models. The study also identifies the major drivers and obstacles faced by the industry, a clear understanding of which might facilitate the formulation of appropriate nation‐wide reverse logistics policy and strategy through the support of the government and the investment of the manufacturers.

The purpose of this paper is to develop an automated disassembly cell that is flexible and robust to the physical variations of a product. In this way it is capable of dealing with any model of product, regardless of the level of detail in the supplied information.

The concept of cognitive robotics is used to replicate human level expertise in terms of perception and decision making. As a result, difficulties with respect to the uncertainties and variations of the product in the disassembly process are resolved.

Cognitive functions, namely reasoning and execution monitoring, can be used in basic behaviour control to address problems in variations of the disassembly process due to variations in the product's structure particularly across different models of the product.

The paper provides a practical approach to formulating the disassembly domain and behaviour control of the cognitive robotic agent via a high‐level logical programming language that combines domain‐specific heuristic knowledge with search to deal with variations in products and uncertainties that arise during the disassembly process.

Full disassembly automation that is flexible and robust to the uncertainties that may arise potentially replaces human labour in a difficult and hazardous task. Consequently, the disassembly process will be more economically feasible, especially in developed countries.

The paper provides a practical approach to the basic cognitive functions that replicate the human expert's behaviour to the disassembly cell.

The purpose of this paper is to improve the automation of selective disassembly sequence planning (SDSP) and generate the optimal or near-optimal disassembly sequences.

The disassembly constraints is automatically extracted from the computer-aided design (CAD) model of products and represented as disassembly constraint matrices for DSP. A new disassembly planning model is built for computing the optimal disassembly sequences. The immune algorithm (IA) is improved for finding the optimal or near-optimal disassembly sequences.

The workload for recognizing disassembly constraints is avoided for DSP. The disassembly constraints are useful for generating feasible and optimal solutions. The improved IA has the better performance than the genetic algorithm, IA and particle swarm optimization for DSP.

All parts must have rigid bodies, flexible and soft parts are not considered. After the global coordinate system is given, every part is disassembled along one of the six disassembly directions –X, +X, –Y, +Y, –Z and +Z. All connections between the parts can be removed, and all parts can be disassembled.

The disassembly constraints are extracted from CAD model of products, which improves the automation of DSP. The disassembly model is useful for reducing the computation of generating the feasible and optimal disassembly sequences. The improved IA converges to the optimal disassembly sequence quickly.

The purpose of this paper is to enhance the method developed by previous researchers. In addition to using the combined interference matrix, the combined connection matrix and the combined contact matrix of product components, the disassembly sequence matrix and the combined instability matrix with platform to evaluate instability of sub‐assemblies are built, and effects of changes of sub‐assembly disassembly directions or tools and the effect of gravity are considered to obtain the best disassembly sequence for a product with many components. A computer program is generated and results of two cases are compared with those of the available studies.

The methodology includes the combined interference matrix, the combined contact matrix and the combined connection matrix of components for a product. The combined instability matrix of sub‐assemblies, changes of sub‐assembly disassembly direction or tools, and the effect of gravity during operation are considered. The binary number system is used to simplify relations among components of a product.

This methodology enhances the existing method and software is generated. Results of two cases are compared and show the same optimum disassembly processes as those obtained from other researchers.

All matrices are defined by the directions of x, y and z with three axes perpendicular to each other. The computer program generated cannot be used for a product with components that must be disassembled in the directions different from the axes.

Two cases are used to investigate feasibility of the proposed methodology with the computer program generated. The first one is an electric drill, and the second one is a flash lighter.

The methodology described in this paper is feasible for study of disassembly processes of products. The software generated can be used to obtain the optimum disassembly process of products.