Optimal disassembly sequence generation and disposal of parts using stability graph cut-set method for End of Life product

Murali, Gunji Bala; Pabba, Sai Krishna; Rajaram, Inder Raj Singh; Sorakayala, Paul Satwik; Dubey, Arnav; Deepak, B. B. V. L.; Biswal, Bibhuti Bhusan; Bahubalendruni, M. V. A. Raju

doi:10.1007/s12046-020-01525-9

Cited by 12 publications

(11 citation statements)

References 27 publications

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“…Wilson and Goffnett [34] focus on RLs activities for EOL products considering the environment and societal issues. Gunji et al [35] studied about optimization of the disassembly sequence for EOL products. Mamaghani and Boucher [36] investigated on recovery optimization of EOL products and considered reducing CO 2 emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

Designing Sustainable Recovery Network of End-of-Life Product during the COVID-19 Pandemic: A Real and Applied Case Study

Abbasi

Daneshmand-Mehr

Kanafi

2022

Discrete Dynamics in Nature and Society

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One of the most important aspects of supply chain management (SCM) is the recovery network (RN), which covers all activities associated with return products (such as collection, recovery, repair, recycling, and waste disposal). Our goal in this paper is to provide a new mathematical model of sustainable end-of-life management (SEOLM) during the COVID-19 pandemic for readers. The suggested recovery network model (RNM) can explain the trade-offs between economic (minimizing total costs), environmental (minimizing bad environmental impacts), and social (minimizing bad social impacts) aspects during the pandemic and the great lockdown. A new RN can be designed with a sustainable and hygienic design when taking environmental, economic, and social considerations into account. It proposes guidelines for managers and scholars on how to address recovery network design (RND) challenges during the pandemic through a mathematical article with a sustainable approach. The scalarization approach of a multi-objective mixed-integer programming (MOMIP) problem in this paper is the weighted sum method. The validation of the presented model and the related Pareto frontier has been illustrated by a case study and numerical example. To perform the optimization process, Lingo software is used.

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Section: Literature Reviewmentioning

confidence: 99%

Designing Sustainable Recovery Network of End-of-Life Product during the COVID-19 Pandemic: A Real and Applied Case Study

Abbasi

Daneshmand-Mehr

Kanafi

2022

Discrete Dynamics in Nature and Society

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“…According to Table 3, there are tool conflicts among Part 14, Part 18, and Part 30. The corresponding APD disassembly sequence can be expressed as K = fk 1 , k 2 , k 3 g: 32,22,23,25,36,21,35,20,34,31,19,10,12,13,11,9,38,8,30,18,40,37,14,26,16,29,24,27,28,39,7,17,2,4,3,1,5,6,15, 41…”

Section: Case Studymentioning

confidence: 99%

“…Gulivindala et al 19 proposed a heuristic method by introducing a novel stability concept and developed a stability matrix by defining a wide variety of stabilities between mating parts to de effective subassemblies for performing parallel assembly sequence planning. Gunji et al 20 used a stability graph cut-set method to generate the disassembly sequence. Then used the reverse of the obtained optimal assembly sequences to generate the optimal disassembly sequences.…”

Section: Introductionmentioning

confidence: 99%

Asynchronous parallel disassembly sequence planning method of complex products using discrete multi-objective optimization

Qiu

Dong

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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Disassembly is a necessary link to realize the integrity of product life cycle. Asynchronous Parallel Disassembly (APD) is an important way to achieve efficient disassembly. Due to the asynchronous start of disassembly tasks by operators in APD, the calculation complexity of disassembly sequence planning optimization increases more obviously with the increase of product complexity. Further, the disassembly sequence is a discrete numerical value, which is difficult to be efficiently realized by existing optimization algorithms. To overcome these difficulties, we introduced a complex products APD description. It helped to describe the APD problem with multiple disassembly resources. Based on the APD resources overall matrix, a three-objective, viz., the total disassembly time-consuming, the disassembly direction change times, and the disassembly tools replacement times, optimization model was constructed. To obtain the optimal disassembly planning sequence, the improved discrete NSGA-II (IDNSGA-II) was proposed, which introduced a novel population restart mechanism. The proposed method was verified in a bevel gearbox disassembly process from the EAS4633 rescue inspection equipment. The optimal results showed the APD sequence planning multi-objective optimized results obtained by the IDNSGA-II algorithm can be close to the single object optimized results. For the rest objects, the optimal solution obtained from the multi-objective genetic algorithm is obviously better.

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“…Zhang et al 5 proposed a precedence-based disassembly subsetgeneration method to solve the CDSP problem. Gunji et al 6 adopted a stability graph cut-set method to generate optimal disassembly sequences of CDSP by considering the minimum number of directional changes as a fitness equation. Bahubalendruni and Varupala 7 aimed to develop an automated optimal CDSP methodology to solve any product configuration.…”

Section: Introductionmentioning

confidence: 99%

An improved multi-objective evolutionary algorithm for multiple-target asynchronous parallel selective disassembly sequence planning

Sun

Guo

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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The product’s service life has been shortened rapidly along with the development of modern technologies and human esthetic evolutions, resulting in a great number of end-of-life (EOL) products. Disassembling renewable parts from EOL products for remanufacturing is of great significance to save resources and protect the environment. The existing studies on selective disassembly sequence planning (SDSP) largely focus on the sequential disassembly planning, which is inefficient especially for complex products because it is a linear process where only one component can be removed at a time. Thus, this work focuses on parallel SDSP and further proposes a multiple-target asynchronous parallel selective DSP (APSDSP) with the objectives of minimizing disassembly time and maximizing disassembly profit simultaneously. In APSDSP, operators can remove multiple components simultaneously as long as disassembly constraints are not violated, and without synchronization requirement between operators. The feasible disassembly sequence and disassembly direction sequence are generated by a space interference matrix method (SIMM) to meet the actual disassembly environment. Based on SIMM, an improved multi-objective evolutionary algorithm based on multiple neighborhood search strategy is developed to create the pareto frontier of the problem. Finally, two cases study are presented to validate the effectiveness of the proposed methodology. It gives enterprises new insights to reduce disassembly time and improve disassembly profit.

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Optimal disassembly sequence generation and disposal of parts using stability graph cut-set method for End of Life product

Cited by 12 publications

References 27 publications

Designing Sustainable Recovery Network of End-of-Life Product during the COVID-19 Pandemic: A Real and Applied Case Study

Designing Sustainable Recovery Network of End-of-Life Product during the COVID-19 Pandemic: A Real and Applied Case Study

Asynchronous parallel disassembly sequence planning method of complex products using discrete multi-objective optimization

An improved multi-objective evolutionary algorithm for multiple-target asynchronous parallel selective disassembly sequence planning

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