Research Papers

A Charts-Based Approach to Estimate Disassembly Time: Hypothesis, Model and Validation

[+] Author and Article Information
Yang Hu

School of Mechanical and Materials Engineering,
Washington State University,
Pullman, WA 99164

Gaurav Ameta

School of Mechanical and Materials Engineering,
Washington State University,
Pullman, WA 99164
e-mail: gaurav.ameta@nist.gov

1Present address: 100 Dairy Dr., National Institute of Standards and Technology, Gaithersburg, MD 20878.

Manuscript received April 27, 2018; final manuscript received November 26, 2018; published online December 24, 2018. Assoc. Editor: Sara Behdad.

J. Manuf. Sci. Eng 141(2), 021009 (Dec 24, 2018) (13 pages) Paper No: MANU-18-1275; doi: 10.1115/1.4042107 History: Received April 27, 2018; Revised November 26, 2018

The purpose of this research is to present a generic method to estimate product disassembly time at detail stage by utilizing Boothroyd and Dewhurst classification form. Disassembly time is critical in decision-making process of end-of-life (EOL) operations, such as reuse, recycling, and remanufacturing. Theoretical assembly time for a design can be estimated using well-established Boothroyd and Dewhurst's method, given an assembly sequence. This method breaks single component assembly time into acquisition time, manual time, and insertion time. However, in disassembly processes, component symmetry features are, in most cases, unnecessary. Based on this fact, a hypothesis is made that a component's disassembly time can be estimated by considering replacing time, part removal time, and elements of surrounding components, including visibility, accessibility, and any additional effort. Fastening component disassembly time can be estimated by replacement time and time consumed by thread number. An assembly model is designed to verify this hypothesis with a predefined disassembly sequence. Totally, 31 undergraduate students took part in the manual assembly and disassembly experiment. Difference between theoretical and manual assembly times was found to be 7.4% while the difference between theoretical and manual disassembly times was 2.4%. Statistical evaluation indicated that the theoretical disassembly time falls within manual disassembly time with 95% confidence interval. To further validate the methods, two case studies are carried out with distinct products under same experimental environment. The approach proposed in this study can estimate disassembly time of a product at detail design stage when disassembly sequence is provided. Future work will focus on automating this method while incorporating selective and destructive disassembly time estimations.

Copyright © 2019 by ASME
Your Session has timed out. Please sign back in to continue.


Rose, C. M. , Beiter, K. A. , and Ishii K. , 1999, “ Determining End-of-Life Strategies as a Part of Product Definition,” IEEE International Symposium on Electronics and the Environment (ISEE), Danvers, MA, May 13, pp. 219–224.
Srinivasan, R. , 2011, “ Sustainability Analysis and Connective Complexity Method for Selective Disassembly Time Prediction,” M.S. thesis, Washington State University, Pullman, WA. http://www.dissertations.wsu.edu/Thesis/Fall2011/r_srinivasan_020712.pdf
Glavič, P. , and Lukman, R. , 2007, “ Review of Sustainability Terms and Their Definitions,” J. Cleaner Prod., 15(18), pp. 1875–1885. [CrossRef]
Subramani, A. K. , and Dewhurst, P. , 1991, “ Automatic Generation of Product Disassembly Sequences,” CIRP Ann., 40(1), pp. 115–118.
Bogue, R. , 2007, “ Design for Disassembly: A Critical Twenty-First Century Discipline,” Assem. Autom., 27(4), pp. 285–289. [CrossRef]
Harjula, T. , Rapoza, B. , Knight, W. A. , and Boothroyd G. , 1996, “ Design for Disassembly and the Environment,” CIRP Ann., 45(1), pp. 109–114. [CrossRef]
Cappelli, F. , Delogu, M. , Pierini, M. , and Schiavone, F. , 2007, “ Design for Disassembly: A Methodology for Identifying the Optimal Disassembly Sequence,” J. Eng. Des., 18(6), pp. 563–575. [CrossRef]
Gupta, S. K. , Regli, W. C. , Das, D. , and Nau, D. S. , 1997, “ Automated Manufacturability Analysis: A Survey,” Res. Eng. Des., 9(3), pp. 168–190. [CrossRef]
Kroll, E. , 1996, “ Application of Work-Measurement Analysis to Product Disassembly for Recycling,” Concurrent Eng., 4(2), pp. 149–158. [CrossRef]
Kroll, E. , and Carver, B. S. , 1999, “ Disassembly Analysis Through Time Estimation and Other Metrics,” Rob. Comput.-Integr. Manuf., 15(3), pp. 191–200. [CrossRef]
Zandin, K. B. , 2002, MOST Work Measurement Systems, 3rd ed., CRC Press, New York.
Desai, A. , and Mital, A. , 2003, “ Evaluation of Disassemblability to Enable Design for Disassembly in Mass Production,” Int. J. Ind. Ergonom., 32(4), pp. 265–281. [CrossRef]
Kroll, E. , Beardsley, B. , and Parulian, A. , 1996, “ A Methodology to Evaluate Ease of Disassembly for Product Recycling,” IIE Trans., 28(10), pp. 837–845. [CrossRef]
Zussman, E. , Kriwet, A. , and Seliger, G. , 1994, “ Disassembly-Oriented Assessment Methodology to Support Design for Recycling,” CIRP Ann.-Manuf. Technol., 43(1), pp. 9–14. [CrossRef]
Yi, H. C. , Park, Y. C. , and Lee, K. S. , 2003, “ A Study on the Method of Disassembly Time Evaluation of a Product Using Work Factor Method,” IEEE International Conference on Systems, Man and Cybernetics, Washington, DC, Oct. 8, pp. 1753–1759.
Zhang, H. C. , Kuo, T. C. , Lu, H. , and Huang, S. H. , 1997, “ Environmentally Conscious Design and Manufacturing: A State of the Art Survey,” J. Manuf. Syst., 16(5), pp. 352–371. [CrossRef]
Lambert, A. J. D. , and Gupta, S. M. , 2005, Disassembly Modeling for Assembly, Maintenance, Reuse and Recycling, CRC Press, London.
Lambert, A. J. D. , 2003, “ Disassembly Sequencing: A Survey,” Int. J. Prod. Res., 41(16), pp. 3721–3759. [CrossRef]
Smith, S. , and Hung, P. , 2015, “ A Novel Selective Parallel Disassembly Planning Method for Green Design,” J. Eng. Des., 26(10–12), pp. 283–301. [CrossRef]
Smith, S. , Smith, G. , and Chen, W. , 2012, “ Disassembly Sequence Structure Graphs: An Optimal Approach for Multiple-Target Selective Disassembly Sequence Planning,” Adv. Eng. Inf., 26(2), pp. 306–316. [CrossRef]
Sanchez, B. , and Haas, C. , 2018, “ A Novel Selective Disassembly Sequence Planning Method for Adaptive Reuse of Buildings,” J. Cleaner Prod., 183, pp. 998–1010. [CrossRef]
Homem de Mello, L. S. , and Sanderson, A. C. , 1990, “ AND/OR Graph Representation of Assembly Plans,” IEEE Trans. Rob. Autom., 6(2), pp. 188–199. [CrossRef]
Dutta, D. , and Woo, T. C. , 1995, “ Algorithm for Multiple Disassembly and Parallel Assemblies,” ASME J. Manuf. Sci. Eng., 117(1), pp. 102–109.
Homem de Mello, L. S. , and Sanderson, A. C. , 1988, “ Automatic Generation of Mechanical Assembly Sequences,” Carnegie Mellon University, Pittsburg, PA, Report No. ADA204234. https://apps.dtic.mil/docs/citations/ADA204234
Mathur, R. K. , Munger, R. , and Sanderson, A. C. , 1992, “ Hierarchical Planning for Space-Truss Assembly,” Intelligent Robotic Systems for Space Exploration, A. Desrochers , ed., Springer, New York, p. 345.
Boothroyd, G. , Dewhurst, P. , and Knight, W. A. , 2011, Product Design for Manufacture and Assembly, CRC Press, Boca Raton, FL.
Mathieson, J. L. , Wallace, B. A. , and Summers, J. D. , 2013, “ Assembly Time Modelling Through Connective Complexity Metrics,” Int. J. Comput. Integr. Manuf., 26(10), pp. 1–13. [CrossRef]
Miller, M. G. , Summers, J. D. , Mathieson, J. L. , and Mocko, G. M. , 2014, “ Manufacturing Assembly Time Estimation Using Structural Complexity Metric Trained Artificial Neural Networks,” ASME J. Comput. Inf. Sci. Eng., 14(1), p. 011005. [CrossRef]
Owensby, J. E. , and Summers, J. D. , 2014, “ Assembly Time Estimation: Assembly Mate Based Structural Complexity Metric Predictive Modeling,” ASME J. Comput. Inf. Sci. Eng., 14(1), p. 011004. [CrossRef]
Das, S. K. , and Naik, S. , 2002, “ Process Planning for Product Disassembly,” Int. J. Prod. Res., 40(6), pp. 1335–1355. [CrossRef]
Rakshit, S. , and Akella, S. , 2015, “ The Influence of Motion Path and Assembly Sequence on the Stability of Assemblies,” IEEE Rob.: Sci. Syst., 12(2), pp. 615–627.
Kongar, E. , and Gupta, S. M. , 2006, “ Disassembly Sequencing Using Genetic Algorithm,” Int. J. Adv. Manuf. Technol., 30(5–6), pp. 497–506. [CrossRef]
Gungor, A. , and Gupta, S. M. , 1998, “ Disassembly Sequence Planning for Products With Defective Parts in Product Recovery,” Comput. Ind. Eng., 35(1–2), pp. 161–164. [CrossRef]
Gupta, S. M. , and McLean, C. R. , 1996, “ Disassembly of Products,” Comput. Ind. Eng., 31(1–2), pp. 225–228. [CrossRef]
Lee, K. , and Gadh, R. , 1998, “ Destructive Disassembly to Support Virtual Prototyping,” IIE Trans., 30(10), pp. 959–972.
Reap, J. , and Bras, B. , 2002, “ Design for Disassembly and the Value of Robotic Semi-Destructive Disassembly,” ASME Paper No. DETC2002/DFM-34181.
Song, X. , Zhou, W. , Pan, X. , and Feng, K. , 2014, “ Disassembly Sequence Planning for Electro-Mechanical Products Under a Partial Destructive Mode,” Assem. Autom., 34(1), pp. 106–114. [CrossRef]
Puente, S. T. , Torres, F. , Reinoso, O. , and Paya, L. , 2010, “ Disassembly Planning Strategies for Automatic Material Removal,” Int. J. Adv. Manuf. Technol., 46(1–4), pp. 339–350. [CrossRef]
Vongbunyong, S. , Kara, S. , and Pagnucco, M. , 2013, “ Application of Cognitive Robotics in Disassembly of Products,” CIRP Ann.-Manuf. Technol., 62(1), pp. 31–34. [CrossRef]
Hu, Y. , Srinivasan, R. , Spoll, J. , and Ameta, G. , 2013, “ Graph Based Method and Tool for Complete and Selective Disassembly Time Estimation in Early Design,” ASME J. Comput. Inf. Sci. Eng., 15(3), p. 031005. [CrossRef]
Whitney, D. E. , 2004, Mechanical Assemblies: Their Design, Manufacture, and Role in Product Development, Oxford University Press, Oxford, UK.
Smith, C. , 1990, Carroll Smith's Nuts, Bolts, Fasteners, and Plumbing Handbook, MotorBooks/MBI Publishing Company, St. Paul, MN.
Ross, S. , 2009, A First Course in Probability, 8th ed., Pearson, Upper Saddle River, NJ.
Gehin, A. , Zwolinski, P. , and Brissaud, D. , 2008, “ A Tool to Implement Sustainable End-of-Life Strategies in the Product Development Phase,” J. Cleaner Prod., 16(5), pp. 566–576. [CrossRef]


Grahic Jump Location
Fig. 1

Alpha and beta rotational symmetries for various parts (adapted from Ref. [26])

Grahic Jump Location
Fig. 2

Experiment environment layout

Grahic Jump Location
Fig. 3

Components, screws, and screwdrivers preparation

Grahic Jump Location
Fig. 4

Manufactured parts assembly model

Grahic Jump Location
Fig. 5

Comparison of theoretical times and manual times with 95% confidence error bar

Grahic Jump Location
Fig. 6

Comparison of theoretical times and manual times with 99% confidence error bar

Grahic Jump Location
Fig. 7

Dance monkey layout

Grahic Jump Location
Fig. 8

Layout of yellow toy



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In