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Research Papers

Leveraging Virtual Reality Experiences With Mixed-Integer Nonlinear Programming Visualization of Disassembly Sequence Planning Under Uncertainty

[+] Author and Article Information
Sara Behdad

Department of Mechanical and
Aerospace Engineering,
Department of Industrial and
Systems Engineering,
University at Buffalo, SUNY,
Buffalo, NY 14260
e-mail: sarabehd@buffalo.edu

Leif P. Berg

Mechanical Engineering Department,
Iowa State University,
Ames, IA 50010
e-mail: lpberg@iastate.edu

Deborah Thurston

Industrial and Enterprise Systems
Engineering Department,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801
e-mail: thurston@illinois.edu

Judy Vance

Department of Mechanical Engineering,
Iowa State University,
Ames, IA 50010
e-mail: jmvance@iastate.edu

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received May 9, 2012; final manuscript received December 18, 2013; published online February 26, 2014. Assoc. Editor: Michael Kokkolaras.

J. Mech. Des 136(4), 041005 (Feb 26, 2014) (8 pages) Paper No: MD-12-1247; doi: 10.1115/1.4026463 History: Received May 09, 2012; Revised December 18, 2013

Disassembly sequence planning at the early conceptual stage of design leads to enormous benefits including simplification of products, lower assembly and disassembly costs, and design modifications which result in increased potential profitability of end-of-life salvaging operations. However, in the early design stage, determining the best disassembly sequence is challenging. First, the required information is not readily available and very time-consuming to gather. In addition, the best solution is sometimes counterintuitive, even to those with experience and expertise in disassembly procedures. Integrating analytical models with immersive computing technology (ICT) can help designers overcome these issues. A two-stage procedure for doing so is introduced in this paper. In the first stage, a stochastic programming model together with the information obtained through immersive simulation is applied to determine the optimal disassembly sequence, while considering uncertain outcomes, such as time, cost, and the probability of causing damage. In the second stage, ICT is applied as a tool to explore alternative disassembly sequence solutions in an intuitive way. The benefit of using this procedure is to determine the best disassembly sequence, not only by solving the analytic model but also by capturing human expertise. The designer can apply the obtained results from these two stages to analyze and modify the product design. An example of a Burr puzzle is used to illustrate the application of the method.

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References

Figures

Grahic Jump Location
Fig. 1

A schematic view of the two-stage procedure of disassembly sequence planning

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Fig. 5

The disassembly graph and the optimum sequence derived from the mathematical model

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Fig. 4

The boxplot of the number of collision for disassembly transition 4

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Fig. 3

Feasible disassembly operations of six-piece Burr puzzle in the form of disassembly graph

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Fig. 2

A Burr puzzle with six interlocking pieces

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