A Hybrid Disassembly Sequence Planning Approach for Maintenance

2002 ◽  
Vol 2 (1) ◽  
pp. 28-37 ◽  
Author(s):  
J. R. Li , ◽  
S. B. Tor , and ◽  
L. P. Khoo
Keyword(s):  
Fitness Function ◽  
Hybrid Approach ◽  
Search Space ◽  
Disassembly Sequence Planning ◽  
Sequence Planning ◽  
Constraint Graph ◽  
Planning Approach ◽  
Disassembly Sequence

This paper describes a hybrid approach to handle disassembly sequence planning for maintenance. The product under maintenance is first modeled using a novel hybrid graph known as Disassembly Constraint Graph (DCG) which embodies complete disassembly information and can be used to prune the search space of disassembly sequences. Subsequently, a novel Tabu-enhanced GA engine is invoked to generate the near optimal disassembly sequences. A case study was used to illustrate the effectiveness of the proposed approach. The details of the DCG, the TS-enhanced GA engine and the fitness function used are presented in this paper.

A disassembly sequence planning approach with an advanced immune algorithm

2012 ◽  
Vol 226 (11) ◽  
pp. 2739-2749 ◽  
Author(s):  
Cong Lu ◽  
Ya-Chao Liu
Keyword(s):  
Single Parent ◽  
Immune Algorithm ◽  
Planning Problem ◽  
Disassembly Sequence Planning ◽  
Sequence Planning ◽  
Planning Approach ◽  
Disassembly Sequence ◽  
Support Matrix ◽  
The Stability

This article proposes a disassembly sequence planning approach with an advanced immune algorithm. First, an enhanced support matrix considering the fasteners is constructed to represent the stability of a product, by which the method to derive the stability of parts in the product is given, and this stability is considered as one of the evaluation objectives in disassembly sequence planning. Second, the immune algorithm is improved to solve the disassembly sequence planning problem, where, a multiple single-parent mutation method is used to replace the crossover; two kinds of vaccines are extracted in two ways and inoculated with different probabilities, and the elite metabolism is used to ensure the effectiveness of the antibodies and also maintain the diversity of the population. Finally, the influence of different factors such as the vaccine extraction interval, the inoculation probability, elite metabolism probability on the evolution performance of the algorithm is investigated, and the validity of the proposed approach is verified through a case study.

scholarly journals Disassembly Sequence Planning (DSP) Applied to a Gear Box: Comparison between Two Literature Studies

2020 ◽  
Vol 10 (13) ◽  
pp. 4591 ◽  
Author(s):  
Leonardo Frizziero ◽  
Alfredo Liverani
Keyword(s):  
Three Dimensional ◽  
Evaluation Criteria ◽  
Three Dimensional Model ◽  
Specific Component ◽  
Disassembly Sequence Planning ◽  
Sequence Planning ◽  
New Methods ◽  
Disassembly Sequence ◽  
Mechanical Products

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.

scholarly journals Disassembly Sequence Planning for Intelligent Manufacturing Using Social Engineering Optimizer

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 663
Author(s):  
Cheng Zhang ◽  
Amir Mohammad Fathollahi-Fard ◽  
Jianyong Li ◽  
Guangdong Tian ◽  
Tongzhu Zhang
Keyword(s):  
Fitness Function ◽  
Evaluation Criteria ◽  
Social Engineering ◽  
Optimization Methods ◽  
Intelligent Manufacturing ◽  
Constraint Matrix ◽  
Disassembly Sequence Planning ◽  
Sequence Planning ◽  
Disassembly Sequence ◽  
Product Disassembly

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.

Adaptive Disassembly Sequence Planning for VR Maintenance Training via Deep Reinforcement Learning

2021 ◽  
Author(s):  
Haoyang Mao ◽  
Zhenyu Liu ◽  
Chan Qiu
Keyword(s):  
Reinforcement Learning ◽  
Fitness Function ◽  
Training System ◽  
Credit Assignment ◽  
Disassembly Sequence Planning ◽  
Rapid Repair ◽  
Sequence Planning ◽  
Disassembly Sequence ◽  
Markov Decision ◽  
Maintenance Work

Abstract Given the great inconvenience caused by the randomness of the fault to the maintenance work, it is necessary to perform on-site and efficient disassembly planning for the faulty parts and present them in combination with virtual reality (VR) technology to achieve rapid repair. As a promising method in solving dynamistic and stochastic problems, deep reinforcement learning (DRL) is adopted in this paper for the solution of adaptive disassembly sequence planning (DSP) in the VR maintenance training system, in which sequences can be generated dynamically based on user inputs. Disassembly Petri net is established to describe and model the disassembly process, and then the DSP problem is defined as a Markov decision process (MDP) that can be solved by the deep Q-network (DQN). For handling the temporal credit assignment with sparse rewards, the long-term return in DQN is replaced with the fitness function of the genetic algorithm (GA). Meanwhile, the update method of gradient descent in DQN is adopted to speed up the iteration of the population in GA. A case study has been conducted to prove that the proposed method can provide better solutions for DSP problems in terms of VR maintenance training.

scholarly journals Electric Vehicle Battery Disassembly Sequence Planning Based on Frame-Subgroup Structure Combined with Genetic Algorithm

2020 ◽  
Vol 6 ◽  
Author(s):  
Qingdi Ke ◽  
Peng Zhang ◽  
Lei Zhang ◽  
Shouxu Song
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Solution Space ◽  
Disassembly Sequence Planning ◽  
Sequence Planning ◽  
Subgroup Structure ◽  
Disassembly Sequence ◽  
Electric Vehicle Battery ◽  
Crossover And Mutation

Since the electric vehicle battery (EVB) is wildly recycled in industry, the disassembly procedures of variable EVBs is so important that can influence the efficiency and environmental impacts in remanufacturing. To improve disassembly efficiency in EVB remanufacturing, a disassembly sequence planning method based on frame-subgroup structure is proposed in this paper. Firstly, the improved disassembly relation hybrid graph and disassembly relation matrix are proposed to identify the disassembly precedence relationship and connection relationship between the components in EVB. Secondly, the frame - subgroup structure is given, and the method for solving disassembly sequence planning with frame-subgroup structure and genetic algorithm is introduced. In this method, to simplify the series of processes such as encoding, decoding, crossover and mutation, the solution space composed of all disassembly sequences is transformed into the positive integer sequence for the disassembly efficiency in battery remanufacturing. Finally, the case study of EVB disassembly sequence planning is presented to validate the feasibility of this proposed method. Comparing with other traditional methods, the advantage and application of this proposed method are introduced.

Research on the Disassembly Sequence Planning for Mechanical Product

2011 ◽  
Vol 80-81 ◽  
pp. 1300-1304 ◽  
Author(s):  
Shi Jie Su ◽  
Xi Feng Fang ◽  
Fang Li
Keyword(s):  
Directed Graph ◽  
Graph Algorithm ◽  
Lubricating Oil ◽  
Prototype System ◽  
Disassembly Sequence Planning ◽  
Sequence Planning ◽  
3D Cad ◽  
Disassembly Sequence ◽  
Mechanical Products

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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