Abstract
Minimization of adverse environmental effect by generated e-waste day to day became challenging in different sectors of both developed and underdeveloping countries. Promoting 3’Rs policy such as reuse, resale, and remanufacture from the EOL products found as an only possible solution for the encountered challenge. An efficient disassembly sequence plan is needed to perform necessary operations and sorting out the relevant parts from EOL products. In order to achieve this, different existing methods have been studied and observed that subassembly identification is most essential in disassembly sequence planning to formulate an efficient solution. But the involvement of more computational effort in SI-based DSP got less research interest. Part concatenation method in ASG proved for generation in ample amount of subassemblies besides ASP. In this paper, a novel attempt has been made by implementing PCM to perform DSP. The results indicated that the method has tremendous workability not only in DSP but also extendable to PDSP, SDSP, and CDSP. The working of PCM on various classifications in DSP is explained with a case study and described well with suitable illustrations.
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References
Kiddee P, Naidu R, Wong MH (2013) Electronic waste management approaches: an overview. Waste Manage 33(5):1237–1250
Harivardhini S, Krishna KM, Chakrabarti A (2017) An integrated framework for supporting decision making during early design stages on end-of-life disassembly. J Clean Prod 168:558–574
Smith SS, Chen WH (2011) Rule-based recursive selective disassembly sequence planning for green design. Adv Eng Inform 25(1):77–87
Ilgin MA, Gupta SM (2010) Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art. J Environ Manage 91(3):563–591
Santochi M, Dini G, Failli F (2002) Disassembly for recycling, maintenance and remanufacturing: state of the art and perspectives. In: AMST’02 advanced manufacturing systems and technology. Springer, Vienna, pp 73–89
Harivardhini S, Chakrabarti A (2016) A new model for estimating end-of-life disassembly effort during the early stages of product design. Clean Technol Environ Policy 18(5):1585–1598
Dini G, Santochi M (1992) Automated sequencing and subassembly detection in assembly planning. CIRP Ann 41(1):1–4
Smith S, Smith G, Chen WH (2012) Disassembly sequence structure graphs: an optimal approach for multiple-target selective disassembly sequence planning. Adv Eng Inform 26(2):306–316
Sinanoğlu C, Rıza Börklü H (2005) An assembly sequence-planning system for mechanical parts using a neural network. Assembly Autom 25(1):38–52
Bahubalendruni MR, Kumar GA (2018) Practically feasible optimal assembly sequence planning with tool accessibility. In: IOP conference series: materials science and engineering, vol 390, no 1. IOP Publishing, Kancheepuram, pp 12–26
Bahubalendruni MR, Biswal BB, Kumar M, Deepak BBVL (2016) A note on mechanical feasibility predicate for robotic assembly sequence generation. In: CAD/CAM, robotics and factories of the future. Springer, New Delhi, pp 397–404
O’shea B, Kaebernick H, Grewal SS (2000) Using a cluster graph representation of products for application in the disassembly planning process. Concurr Eng 8(3):158–170
De Mello LH, Sanderson AC (1991) A correct and complete algorithm for the generation of mechanical assembly sequences. IEEE Trans Robot Autom 7(2):228–240
Baldwin DF, Abell TE, Lui MC, De Fazio TL, Whitney DE (1991) An integrated computer aid for generating and evaluating assembly sequences for mechanical products. IEEE Trans Robot Autom 7(1):78–94
Abdullah MA, Ab Rashid MFF, Ghazalli Z (2018) Optimization of assembly sequence planning using soft computing approaches: a review. Arch Comput Methods Eng 0(0):1–14
Kara S, Pornprasitpol P, Kaebernick H (2005) A selective disassembly methodology for end-of-life products. Assembly Autom 25(2):124–134
Bahubalendruni MR, Gulivindala A, Kumar M, Biswal BB, Annepu LN (2019) A hybrid conjugated method for assembly sequence generation and explode view generation. Assembly Autom 39(1):211–225
Wang X, Qin Y, Chen M, Wang CT (2005) End-of-life vehicle recycling based on disassembly. J Central South Univ Technol 12(2):153–156
Bahubalendruni MR, Biswal BB (2017) A novel concatenation method for generating optimal robotic assembly sequences. Proc Inst Mech Eng Part C J Mech Eng Sci 231(10):1966–1977
Bahubalendruni MR, Biswal BB (2015) An intelligent method to test feasibility predicate for robotic assembly sequence generation. In: Intelligent computing, communication, and devices. Springer, New Delhi, pp 277–283
Bahubalendruni MR, Biswal BB (2016) Liaison concatenation—a method to obtain feasible assembly sequences from the 3D-CAD product. Sadhana 41(1):67–74
Bahubalendruni MR (2018) An efficient method for exploded view generation through assembly coherence data and precedence relations. World J Eng 15(2):248–253
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Gulivindala, A.K., Matta, V.R., Raju Bahubalendruni, M.V.A. (2020). Disassembly Sequence Planning Methodology for EOL Products Through a Computational Approach. In: Deepak, B., Parhi, D., Jena, P. (eds) Innovative Product Design and Intelligent Manufacturing Systems. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2696-1_69
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DOI: https://doi.org/10.1007/978-981-15-2696-1_69
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