Disassembly sequence planning for electro-mechanical products under a partial destructive mode

2014 ◽  
Vol 34 (1) ◽  
pp. 106-114 ◽  
Author(s):  
Xiaowen Song ◽  
Weidong Zhou ◽  
Xingxing Pan ◽  
Kun Feng

Purpose – 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. Design/methodology/approach – 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. Findings – 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. Research limitations/implications – Partial destructive disassembly mode cannot be used for the flammable or explosive component in the procedure of the DSP optimization algorithm. Practical implications – DSP of an electric corkscrew is analyzed to investigate the accuracy and efficiency of the proposed method. Originality/value – 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.

2020 ◽  
Vol 10 (13) ◽  
pp. 4591 ◽  
Author(s):  
Leonardo Frizziero ◽  
Alfredo Liverani

This work aims to analyze the characteristics and importance that design techniques for disassembly assume in the modern design phase of a mechanism. To this end, the study begins by considering a three-dimensional model of a gear motor, taken from the components of which the overall drawings are arranged and from the relief of those not available. Once the mechanism has been digitally reconstructed, the activity focuses on the study of the optimal disassembly sequence by comparing different methodologies, according to two evaluation criteria—minimizing the time taken and minimizing the number of tool changes necessary to complete the sequence. The main results of the work are (1) defining a standard methodology to improve disassembly sequence planning, (2) finding the best disassembly sequence for the specific component among the literature and eventually new methods, and (3) offering to the industrial world a way to optimize maintenance operations in mechanical products. Referring to the limitation of the present works, it can be affirmed that the results are limited to the literature explored and to the case study examined.


Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 663
Author(s):  
Cheng Zhang ◽  
Amir Mohammad Fathollahi-Fard ◽  
Jianyong Li ◽  
Guangdong Tian ◽  
Tongzhu Zhang

Product disassembly and recycling are important issues in green design. Disassembly sequence planning (DSP) is an important problem in the product disassembly process. The core idea is to generate the best or approximately optimal disassembly sequence to reduce disassembly costs and time. According to the characteristics of the DSP problem, a new algorithm to solve the DSP problem is proposed. Firstly, a disassembly hybrid graph is introduced, and a disassembly constraint matrix is established. Secondly, the disassembling time, replacement frequency of disassembly tool and replacement frequency of disassembly direction are taken as evaluation criteria to establish the product fitness function. Then, an improved social engineering optimizer (SEO) method is proposed. In order to enable the algorithm to solve the problem of disassembly sequence planning, a swap operator and swap sequence are introduced, and steps of the social engineering optimizer are redefined. Finally, taking a worm reducer as an example, the proposed algorithm is used to generate the disassembly sequence, and the influence of the parameters on the optimization results is analyzed. Compared with several heuristic intelligent optimization methods, the effectiveness of the proposed method is verified.


2008 ◽  
Vol 71 (13-15) ◽  
pp. 2720-2726 ◽  
Author(s):  
Wang Hui ◽  
Xiang Dong ◽  
Duan Guanghong

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