Model of mobility state of parts: The automation of feasibility test in disassembly sequence generation

Issaoui, Louisa; Aifaoui, Nizar; Benamara, Abdelmajid

doi:10.1177/0954406216654196

Cited by 9 publications

(3 citation statements)

References 46 publications

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“…Smith and Chen (2011) presented a rule-based recursive method for finding a near-optimal heuristic selective disassembly sequence for green design. Issaoui et al (2017) developed a new disassembly direction matrix as the representation model of disassembly directions, which can give information about the mobility state of a part during disassembly sequencing by updating its mobility matrix. Huang and Liao (2009) combined the disassembly sequence matrix and the instability matrix into a disassembly matrix to obtain the best disassembly sequence for a product with many components, in which the effects of changes of sub-assembly disassembly directions or tools and the effect of gravity are Figure 2 The process of DSP considered.…”

Section: Literature Reviewmentioning

confidence: 99%

A hybrid artificial fish swam algorithm for disassembly sequence planning considering setup time

Guo

Zhong

et al. 2018

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Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications DSP of an internal gear hydraulic pump is analyzed to investigate the accuracy and efficiency of the proposed method. Originality/value 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.

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Section: Literature Reviewmentioning

confidence: 99%

A hybrid artificial fish swam algorithm for disassembly sequence planning considering setup time

Guo

Zhong

et al. 2018

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“…In order to increase the revenue when retrieving only some components from a given product, Smith and Chen [10] proposed a rule-based recursive method to find a near-optimal heuristic selective disassembly sequence. Issaoui et al [11] propose a new disassembly direction matrix as a representative model of the disassembly direction, and updated the movement matrix of the parts to provide information about the movement status of the parts during the disassembly sequencing process. Tian et al [12] introduce a conflict matrix in the AOG graph to deal with the exclusive OR problem that the existing heuristic disassembly algorithm cannot solve.…”

Section: Introductionmentioning

confidence: 99%

Disassembly Sequence Planning for Intelligent Manufacturing Using Social Engineering Optimizer

Zhang

Fathollahi-Fard

et al. 2021

Symmetry

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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.

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“…Nevertheless, the fuzzy relationship among the parts was seldom considered during the disassembly module partition, which led to the poor quality of the acquired disassembly modules. Disassembly information modeling expresses the geometric relationship, connection relationship and disassembly constraint relationship among the parts [10]. Moore et al [11] obtained the disassembly precedence matrix from product CAD models and built a disassembly petri net model for recycling and remanufacturing.…”

Section: Introductionmentioning

confidence: 99%

A Novel Modular Disassembly Design Method for CNC Machine Tools based on PSOA and TOPSIS

Feng¹,

Wu²,

Zhai³

et al. 2020

Preprint

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Disassembly is one of the crucial issues for the green remanufacturing of obsolete CNC machine tools. Meanwhile, modular design method is the guarantee of disassembly rationality, which can maximize economic and environmental benefits. However, modular disassembly processes of CNC machine tools are more uncertainty in system structures and component conditions. On the basis of summarizing the existing research, disassembly module modeling of CNC machine tools is implemented. For one advantage, the rough set theory is utilized to cluster the parts into different disassembly modules. For another, disassembly information model is constructed by the disassembly multi-constrained graph. Secondly, multi-objective mathematical model which contains disassembly time, disassembly benefit and disassembly complexity is built. A novel particle swarm optimization algorithm (PSOA) improved by niche technology is applied to the disassembly sequence planning. Last but not least, this work also evaluates the disassembly scheme of CNC machine tools based on the technology for order preference by similarity to an ideal solution (TOPSIS). Evaluation indicator system is established and the comprehensive weight of evaluation indicators is determined by the respective advantages of entropy weight method (EWM) and analytic hierarchy process (AHP). A case study is conducted to illustrate the feasibility of the proposed models and methods. The results of this work can contribute to the selection of the optimal modular disassembly scheme of CNC machine tools.

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Model of mobility state of parts: The automation of feasibility test in disassembly sequence generation

Cited by 9 publications

References 46 publications

A hybrid artificial fish swam algorithm for disassembly sequence planning considering setup time

A hybrid artificial fish swam algorithm for disassembly sequence planning considering setup time

Disassembly Sequence Planning for Intelligent Manufacturing Using Social Engineering Optimizer

A Novel Modular Disassembly Design Method for CNC Machine Tools based on PSOA and TOPSIS

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