Improvement to quality function deployment methodology : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Applied Statistics at Massey University, Palmerston North, New Zealand
Loading...
Date
2017
DOI
Open Access Location
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Massey University
Rights
The Author
Abstract
Quality Function Deployment (QFD) is a quality improvement methodology which
translates true customer requirements into technical solutions. The major purposes in
implementing QFD are enhancing quality, decreasing production cycle time, and
lowering costs. QFD methodology utilises a system of matrix like structures known as
the House of Quality (HOQ) which work collectively to determine final weightings of
the technical characteristics. The derivation of final weights of the technical
characteristics and their prioritisation is the final key in QFD process. One of the main
theoretical difficulties in employing QFD is that it deals with multidimensional
categorical (ordinal) data variables. The rating data of these categorical variables
varies from person to person and case study to case study. In prioritising the technical
characteristics, QFD practitioners often fail to fully integrate the diverse information
extractable from ordinal data and ignore some sections of QFD, House of Quality
(HOQ). It is also observed that in each matrix of QFD-HOQ, numerous heuristics
have been introduced to suppress the variation, uncertainty and vagueness. During the
QFD process, any mistakes such as selection and interpretation of rating scales,
application of methods, or integration of various matrices can fail the whole process.
In this project with the rationale to improve QFD methodology, a systematic emphasis
is placed on the following issues i) Application of methods, procedures, techniques
for the appropriate selection of likert scales within each matrix of QFD-HOQ. ii)
Application to each matrix, data and their integration towards statistically valid
conclusions. iii) Close observation and interpretation of the final prioritisation of
technical characteristics (TCs), and its enhancement.
Description
Content removed from thesis due to copyright restrictions: Iqbal, Z., Grigg, N. P., Govindaraju, K., & Campbell-Allen, N. M. (2016). A distance-based methodology for increased extraction of information from the roof matrices in QFD studies. International Journal of Production Research, 54(11), 3277-3293. doi:10.1080/00207543.2015.1094585
Iqbal, Z., Grigg, N. P., & Govindaraju. (2017). Performing competitive analysis in QFD studies using multipole moments and bootstrap sampling. Quality Engineering, 29(2), 311-321. doi:10.1080/08982112.2016.1181181
Iqbal, Z., Grigg, N. P., Govindaraju, K., & Campbell-Allen, N. (2014). Statistical comparison of final weight scores in quality function deployment (QFD) studies. International Journal of Quality & Reliability Management, 31(2), 184-204. doi:10.1108/IJQRM-06-2013-0092
Iqbal, Z., Grigg, N. P., Govindaraju, K., & Campbell-Allen, N. M. (2015). Enhancing prioritisation of technical attributes in quality function deployment, 64(3), 398-415. doi.10.1108/IJPPM-10-2014-0156
Keywords
Quality function deployment, Methodology