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Research Papers

A Multiple-Domain Matrix Support to Capture Rationale for Engineering Design Changes

[+] Author and Article Information
L. Siddharth

Centre for Product Design and Manufacturing,
Indian Institute of Science,
Bengaluru 560012, India
e-mail: siddharthl@iitrpr.ac.in

Prabir Sarkar

Mechanical Department,
Indian Institute of Technology Ropar,
Rupnagar 140001, India
e-mail: prabir@iitrpr.ac.in

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received October 26, 2017; final manuscript received March 27, 2018; published online April 26, 2018. Assoc. Editor: Rahul Rai.

J. Comput. Inf. Sci. Eng 18(2), 021014 (Apr 26, 2018) (11 pages) Paper No: JCISE-17-1248; doi: 10.1115/1.4039850 History: Received October 26, 2017; Revised March 27, 2018

Design changes are necessary to sustain the product against competition. Due to technical, social, and financial constraints, an organization can only implement a few of many change alternatives. Hence, a wise selection of a change alternative is fundamentally influential for the growth of the organization. Organizations lack knowledge bases to effectively capture rationale for a design change; i.e., identifying the potential effects a design change. In this paper, (1) we propose a knowledge base called multiple-domain matrix that comprises the relationships among different parameters that are building blocks of a product and its manufacturing system. (2) Using the indirect change propagation method, we capture these relationships to identify the potential effects of a design change. (3) We propose a cost-based metric called change propagation impact (CPI) to quantify the effects that are captured from the multiple-domain matrix. These individual pieces of work are integrated into a web-based tool called Vatram. The tool is deployed in a design environment to evaluate its usefulness and usability.

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Copyright © 2018 by ASME
Topics: Design
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Figures

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Fig. 1

Pahl and Beitz [6] design model

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Fig. 2

Clockwise from top-left: (a) product hierarchy, (b) database structure using adjacency list, and (c) DSM [18]

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Fig. 3

Direct change propagation method [20]

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Fig. 4

Indirect change propagation method [21]

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Fig. 5

Indirect change propagation applied in a multiple-domain matrix

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Fig. 6

The multidomain matrix implemented on Stapler

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Fig. 7

Software architecture for Vatram

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Fig. 8

The web page through change input is given by selecting one of the design parameters

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Fig. 9

The representation of impact of a design change

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Fig. 10

Comparison of impact across three design changes

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Fig. 11

Adding a manufacturing parameter

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Fig. 12

Modifying a design parameter

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Fig. 13

Deploying the tool—Vatram in a design environment

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