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RESEARCH PAPERS

Enhancing the Quality Function Deployment Conceptual Design Tool

[+] Author and Article Information
Martin Leary

Department of Mechanical and Manufacturing Engineering,  The University of Melbourne, Parkville 3010, Australia

Colin Burvill1

Department of Mechanical and Manufacturing Engineering,  The University of Melbourne, Parkville 3010, Australiacolb@unimelb.edu.au

As for the term design, quality has various definitions in the literature, for example, (6-7). In this paper, “quality” is defined as “the extent to which the customer’s needs are fulfilled” (8).

Mandatory and negotiable constraints has alternate definitions and nomenclature in the literature, for example, demands and wishes (13) or as hierarchical tree of objectives (14-15).

I.e., fatigue is the dominant failure mode and component failure can cause death or injury (16).

1

Corresponding author.

J. Mech. Des 129(7), 701-708 (Feb 26, 2007) (8 pages) doi:10.1115/1.2722787 History: Received October 27, 2006; Revised February 26, 2007

The quality function deployment (QFD) conceptual design tool has been of significant benefit to customer satisfaction, while reducing the associated design time and cost. Observation of novice designers in tertiary engineering design courses identified a range of impediments to the robust transfer of QFD capabilities to the novice designers. These impediments appear to limit the perceived merit of QFD in novice designers and stymie its subsequent practical application. Given the improved design outcomes associated with QFD, a series of enhancements has been developed to overcome these impediments and assist the robust transfer of QFD capabilities to novice designers. The traditional QFD tool does not engage with customer requirements that constrain the feasibility of a design solution. This limitation restricts the applicability of QFD as an overarching design reference because an additional repository is required to document design constraints and may result in confusion in novice designers and flawed design outcomes if design constraints are used. A novel differential assessment method has been developed to overcome this limitation by enabling the inclusion of design constraints. The outcomes of this paper contribute to design education by facilitating the robust transfer of QFD capabilities and providing novel enhancements that expand the useful outcomes associated with QFD.

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Copyright © 2007 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Generic house of quality (HoQ) template

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Figure 2

Modified HoQ template proposed to mitigate common misunderstandings by the use of a self-explanatory nomenclature and presentation

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Figure 3

Abridged HoQ for a hypothetical rifle, based on the commonly espoused representation. Here, only positive correlations are identified in the CR-TR correlation matrix. This HoQ incorrectly identifies mass as the most influential TR.

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Figure 4

Abridged HoQ for a hypothetical rifle, enhanced to allow positive and negative CR-TR correlations. This HoQ correctly identifies that quality is independent of mass and that telescope magnification is the most influential TR.

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Figure 5

HoQ of CRs and TRs for mass reduction of FLSC ferrous metal automotive components by forged light alloy substitution. Nomenclature: maximize (↑), minimize (↓), target (엯), acceptable cost premium (ACP), objective (O), soft constraint (CS), hard constraint (CH), Australian design rule (ADR), and heat treatment (HT). CR-TR correlation legend: strong positive (9), moderate positive (3), weak positive (1), strong negative (−9), moderate negative (−3), and weak negative (−1).

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Figure 6

Normalized importance of the salient material properties identified with the DA method (Fig. 5). Histogram legend: Normalized technical importance (T-I) (black), normalized constraint importance (C-I) (gray), normalized objective importance (O-I) (white).

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