Object Selective Disassembly Sequence Planning for Complex Mechanical Products

2010 ◽  
Vol 46 (11) ◽  
pp. 172 ◽  
Author(s):  
Xiufen ZHANG
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.


Author(s):  
Shana Smith ◽  
Wei-Han Chen

Modern green products must be easy to disassemble. Selective disassembly is used to access and remove specific product components for reuse, recycling, or remanufacturing. Early related studies developed various heuristic or graph-based approaches for single-target selective disassembly. More recent research has progressed from single-target to multiple-target disassembly, but disassembly model complexity and multiple constraints, such as fastener constraints and disassembly directions, still have not been considered thoroughly. In this study, a new graph-based method using disassembly sequence structure graphs (DSSGs) was developed for multiple-target selective disassembly sequence planning. The DSSGs are built using expert rules, which eliminate unrealistic solutions and minimize graph size, which reduces searching time. Two or more DSSGs are combined into one DSSG for accessing and removing multiple target components. In addition, a genetic algorithm is used to decode graphical DSSG information into disassembly sequences and optimize the results. Using a GA to optimize results also reduces searching time and improves overall performance, with respect to finding global optimal solutions. Case studies show that the developed method can efficiently find realistic near-optimal multiple-target selective disassembly sequences for complex products.


2011 ◽  
Vol 80-81 ◽  
pp. 1300-1304 ◽  
Author(s):  
Shi Jie Su ◽  
Xi Feng Fang ◽  
Fang Li

Mechanical products have been inevitably disassembled when they are regarded to be recycled or repaired. The disassembling procedure must be decided no matter what way is used to disassemble. The key is to decide the disassembly sequence for parts/components. In order to generate the disassembly sequence rapidly and correctly, similar thread binary tree and graph algorithm are used to establish the model of disassembly after analyzing the characteristics of Mechanical products. Firstly, generate the related matrix obtained from the 3D CAD assembly model; secondly, transform the undirected graph to the directed graph based on the practical constraints between parts/components; finally, search the restrictions among the directed graph and generate the efficient disassembly sequence. A prototype system of disassembly sequence planning based on UG was implemented which has the functions such as parts and assembly information extraction, definition constraints between components, disassembly sequence planning and etc. The centrifugal lubricating oil filter case study proves the validity and feasibility of the proposed method.


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