Approach of Composing Disassembly Model Based on the CAD Information for End of Life Product

For the purpose of recycling end of life product, Selective disassembly methods are most common used for dismantling the old product. Only some parts which valuable for remanufacturing or reuse are dismantled. In addition, the optimal disassembly sequence which created automatic by the computer will help to decrease the disassembly cost and increase the whole revenue of recycling process. However, the disassembly model are still cannot be composed by the computer automatic, that is, some of the work need be done manually. Especially, the priority information among the parts should be analyzed by the engineer. In this paper, an automatic method is presented by comparing the feature of the parts. And then, by extracting and analyzing mates in the assembly, the adjacent information is obtained. Adjacency information and priority information respectively expressed by adjacency matrix and influence matrix, which can be used to depict the hybrid graph model in matrix-form, achieving the automatically creation of disassembly hybrid graph model.

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Optimal Modular Remanufactured Product Configuration and Harvesting Planning for End-of-Life Products

10.1115/detc2021-69964 ◽

2021 ◽

Author(s):

Jinju Kim ◽

Seyoung Park ◽

Harrison M. Kim

Keyword(s):

Production Process ◽

End Of Life ◽

New Products ◽

Product Configuration ◽

Target Component ◽

Configuration Design ◽

Customer Demand ◽

Proposed Model ◽

Disassembly Sequence ◽

Selective Disassembly

Abstract Since remanufacturing requires additional processes compared to the production process of new products, various factors need to be considered. First, it is necessary to decide which end-of-life (EoL) product parts/modules to use among the EoL products available for the remanufactured product. At this stage, it is crucial to understand the future customer demand and requirements for each part. Next, it is also necessary to figure out whether selective disassembly is possible to disassemble a specific target component without completely disassembling the product. With the increasing number of product designs that are difficult to disassemble, the disassembly sequence and level should be considered for the efficiency of the overall remanufacturing process. This study proposes an integrated model to (i) find configuration design suitable for remanufactured products that can maximize customer utility based on current EoL products, and (ii) establish a harvest plan that determines the optimal operations and levels. This proposed model can be used as a tool that helps product designers find the appropriate design of remanufactured products while increasing the efficiency of the remanufacturing process.

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Research of Partial Destructive based Selective Disassembly Sequence Planning

The Open Mechanical Engineering Journal ◽

10.2174/1874155x01509010605 ◽

2015 ◽

Vol 9 (1) ◽

pp. 605-612 ◽

Cited By ~ 3

Author(s):

Zhou Ziqiang ◽

Dai Guohong ◽

Zhang Xiangyan ◽

Hu Chaobin ◽

Zhang Yongjian

Keyword(s):

Material Properties ◽

Nondestructive Method ◽

Target Component ◽

Recycling Process ◽

Disassembly Sequence Planning ◽

Material Recycling ◽

Disassembly Sequence ◽

Study Case ◽

Selective Disassembly ◽

The Cost

In the process of recycling EOL (end of life) products, disassembly is an important stage. Moreover, there are several targets for disassembly: reuse, remanufacturing and material recycling. In order to improve the efficiency of disassembly, only the component which need to be reused or remanufactured need to be disassembled with nondestructive method. The rest components which recycled for material can be disassembled with partial destructive method. Namely, partial destructive disassembly is more practical than total disassembly within recycling process for EOL products. In this paper, the generally used partial destructive disassembly methods are analyzed. And several rules are defined for reconstructing the hybrid graph of EOL product. And then, an extended Floyd algorithm is proposed for searching optimized disassembly sequence. With this algorithm, the material properties of parts, connection properties between parts or components are taking into account. By ranking the cost of several possible disassembly path, the optimal disassembly sequence is obtained for target component. At last, a soybean milk machine is used as a study case to verify the former approach.

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Reinforcement Learning-Based Selective Disassembly Sequence Planning for the End-of-Life Products with Structure Uncertainty

IEEE Robotics and Automation Letters ◽

10.1109/lra.2021.3098248 ◽

2021 ◽

pp. 1-1

Author(s):

Xikun Zhao ◽

Congbo Li ◽

Ying Tang ◽

Jiabin Cui

Keyword(s):

Reinforcement Learning ◽

End Of Life ◽

Disassembly Sequence Planning ◽

Sequence Planning ◽

Disassembly Sequence ◽

Selective Disassembly

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A METHODOLOGY TO SUPPORT COMPANIES IN THE FIRST STEPS TOWARDS DE-MANUFACTURING

Proceedings of the Design Society ◽

10.1017/pds.2021.14 ◽

2021 ◽

Vol 1 ◽

pp. 131-140

Author(s):

Federica Cappelletti ◽

Marta Rossi ◽

Michele Germani ◽

Mohammad Shadman Hanif

Keyword(s):

Environmental Impact ◽

End Of Life ◽

Design Stage ◽

Life Strategies ◽

Disassembly Sequence ◽

The Status ◽

The Cost ◽

Technical Solutions ◽

First Time ◽

Complex Activities

AbstractDe-manufacturing and re-manufacturing are fundamental technical solutions to efficiently recover value from post-use products. Disassembly in one of the most complex activities in de-manufacturing because i) the more manual it is the higher is its cost, ii) disassembly times are variable due to uncertainty of conditions of products reaching their EoL, and iii) because it is necessary to know which components to disassemble to balance the cost of disassembly. The paper proposes a methodology that finds ways of applications: it can be applied at the design stage to detect space for product design improvements, and it also represents a baseline from organizations approaching de-manufacturing for the first time. The methodology consists of four main steps, in which firstly targets components are identified, according to their environmental impact; secondly their disassembly sequence is qualitatively evaluated, and successively it is quantitatively determined via disassembly times, predicting also the status of the component at their End of Life. The aim of the methodology is reached at the fourth phase when alternative, eco-friendlier End of Life strategies are proposed, verified, and chosen.

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