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Research Papers: Design Theory and Methodology

Exploring Effective Change Propagation in a Product Family Design

[+] Author and Article Information
Inayat Ullah

College of Mechanical and
Electrical Engineering,
Nanjing University of Aeronautics
and Astronautics,
No. 29 Yudao Street, Qinhaui District,
Nanjing 210016, Jiangsu, China
e-mail: anykhattak@yahoo.com

Dunbing Tang

College of Mechanical and
Electrical Engineering,
Nanjing University of Aeronautics
and Astronautics,
No. 29 Yudao Street, Qinhaui District,
Nanjing 210016, Jiangsu, China
e-mail: d.tang@nuaa.edu.cn

Qi Wang

College of Mechanical and
Electrical Engineering,
Nanjing University of Aeronautics
and Astronautics,
No. 29 Yudao Street, Qinhaui District,
Nanjing 210016, Jiangsu, China
e-mail: wq001115@126.com

Leilei Yin

College of Mechanical and
Electrical Engineering,
Nanjing University of Aeronautics
and Astronautics,
No. 29 Yudao Street, Qinhaui District,
Nanjing 210016, Jiangsu, China
e-mail: yllwyp@163.com

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received January 4, 2017; final manuscript received July 31, 2017; published online October 3, 2017. Assoc. Editor: Scott Ferguson.

J. Mech. Des 139(12), 121101 (Oct 03, 2017) (13 pages) Paper No: MD-17-1009; doi: 10.1115/1.4037627 History: Received January 04, 2017; Revised July 31, 2017

Product family (PF) design is a widely used strategy in the industry, as it allows meeting diverse design requirements. Change propagation in any PF is difficult to predict. Consequently, while numerous design change management methodologies presently exist, their application is restricted to a single artifact. This issue is overcome in the present study. The proposed framework explores effective change propagation paths (CPPs) by considering the risks associated with design changes in the PF with the aim of minimizing the overall redesign cost. The propagated risk, which would result in rework, is quantified in terms of change impact and propagation likelihood. Moreover, a design structure matrix (DSM) based mathematical model and an algorithm for its implementation are proposed to investigate the change propagation across the PF. Finally, to demonstrate their effectiveness, a PF of electric kettles is examined in a case study. The study findings confirm that the proposed technique is appropriate for evaluating different CPPs in PF.

Copyright © 2017 by ASME
Topics: Design , Risk , Algorithms
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Figures

Grahic Jump Location
Fig. 1

Components description in PF

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Fig. 2

Logical relationship between components: (a) OR and (b) AND

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Fig. 3

Components: (a) dependency matrix and (b) logical relationship matrix

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Fig. 5

CPPs based on logic OR and AND

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Fig. 6

Proposed approach for exploring CPPs in PF

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Fig. 7

Change flow pattern in PF

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Fig. 8

Flow chart of searching alternative CPPs in PF

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Fig. 9

Likelihood and change impact matrices: (a) basic, (b) home, (c) office, and (d) business kettle

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Fig. 10

Logical relationships matrices: (a) basic, (b) home, (c) office, and (d) business kettle

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Fig. 11

CPPs analysis based on redesign duration in the business kettle

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Fig. 12

Propagated path in the business kettle

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Fig. 13

CPPs analysis based on redesign duration in the office kettle

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Fig. 14

Propagated path in the office kettle

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Fig. 15

CPPs analysis based on redesign duration in the home kettle

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Fig. 16

Propagated path in the home kettle

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Fig. 17

Propagated path in the PF

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