Section 4 Quality Function Deployment
Quality function deployment (QFD) was invented in the late 1960s at the Kobe
shipyard of Mitsubishi Heavy Industries. As it evolved it become a well-known planning methodology for translating customer needs into relevant technical requirements (Govers, 1996; Hauser & Clausing, 1988). Generally, the QFD is implemented through a matrix called the House of Quality (HoQ) which is a kind of conceptual map that provides the means for interfunctional planning and communications (Hauser & Clausing, 1988). Figure 7 shows the elements for constructing HoQ which are introduced as follows.1. Customer requirements: The construction of the HoQ starts with the determination of the customer requirements (WHATs) which is on the left side of the HoQ. To deploy available resources effectively, all WHATs must be rated against each other to quantify their importance to help set priorities for the product or service development process and provide guidelines.
2. Customer assessment: On the right hand side of the HoQ is the customer assessment part, which contains information on the customer’s perception of the company’s performance compared to competitor’s performance.
3. Technical requirements: The upper side of the HoQ is the technical requirements (TRs/HOWs) part, which gives a technical description of how to realize the consumer requirements.
4. Relationship matrix: The centre part of the HoQ depicts the relationship and strength between each WHAT and TR. This relationship matrix also can be used to indicate that a WHAT has inadequately been translated into a TR.
Figure 7 The house of quality
Note: From “Incorporating cost and environmental factors in quality function deployment using data envelopment analysis,” by R. Ramanathan and J. Yunfeng, Omega, 37(3), p.713.
5. Technical correlation matrix: The correlation matrix, put in the roof of the HoQ, is used to specify the various TRs that have to be improved collaterally, providing a basis to calculate to what extent a change in one feature will affect other features (Karsak, Sozer, & Alptekin, 2002). In other words, its use is to show whether trade-off decisions have to be made.
A. Customer Requirements
CR1 CR2 CR3 CR4 CR5 CR6
Importance of WHATs
♁
♁
△
◎
◎
◎
◎
△
♁
♁
♁
△
◎
◎
◎
△
♁
TR1 TR2 TR3 TR4
C. Technical Requirements
B. Competitive Bench-marketing
E. Technical Correlation Matrix
Absolute importance Relative importance
Rank Cost
Relative importance/cost Rank
F. Technical Matrix
D. Relationship Matrix of WHATs and TRs
♁ Strong relationship (9)
△ Medium relationship (3)
◎ Week relationship (1)
6. Technical matrix: The bottom of the HoQ contains different types of information for making decisions by utilizing the relative importance of each TR in achieving the collective WHATs. The derived importance score of WHATs are then multiplying the weightings in the cells of each row of the interrelationship matrix. Further, the cell scores are summed down each column to assign a relative priority to each TR, and the TR with the greatest score is allocated the highest priorities.
Eventually, to convey the customer's voice through to manufacturing, a serious of houses has to be linked (Hauser & Clausing, 1988). As shown in Figure 8, this process continues to a third and fourth phase as the “HOWs” of one stage become the “WHATs” of the next.
Figure 8 Linked houses convey the customer's voice through to manufacturing
Note: From “The House of Quality,” by J. R. Hauser and D. Clausing, Harvard Business
Review, 66(3), p.73.
Even if QFD is originally used by manufacturing organizations to assist in obtaining a balance between customer needs and the organizations’ actual ability to fulfill the requirements, recent researches started to apply QFD in service industries. For example, on basis of the evaluation of existing service concept design methods, Simons and Bouwman (2006) developed an alternative service concept design method based on QFD to focus on achieving multi-channel synergy by using data from six cases in the insurance and telecommunication industry. Wang (2007) applied the QFD to assist management in
Product requirement
Key process operations IV
Engineering characteristics
Customer attributes I
Parts characteristics
Engineering characteristics II Part
characteristics III
Key process operations
understanding the voice of outside consumer and to better prioritize internal operations in China Airlines. To help analyze the imprecise and subjective problem information, Su and Lin (2008) present a systematic process based on QFD to resolve the problems in the e-commerce industry and develop a systematic procedure to overcome the discrepancies in the problem-formulating process. Moreover, Andronikidis, Georgiou, Gotzamani, and Kamvysi (2009) discussed the integration of quantitative techniques with QFD and promoted successful application of QFD in finical service organizations.
Additionally, to better address the practical implications, in some cases, QFD was adapted or applied together with other methods by recent studies. For example, by arguing there is a paucity of methodologies for deriving the relative importance of design requirements when several additional factors are considered, Ramanathan and Yunfeng (2009) adopted DEA to facilitate QFD computations and applied this new methodology to the design of security fasteners for a Chinese company. Lee and Chen (2009) in another way integrated Kano theory with QFD, and proposed a revised improved ratio to strengthen the rise in customer satisfaction.
In order to clarify the thread of recent QFD-based literatures, the “Abstract” search is employed by using the term “Quality Function Deployment” in ScienceDirect/Online (SDOL) database. 87 articles are found from 2007 to 2011. Retaining the articles from
Social Science related journals (Table 5), the meta-analysis scheme (referred to Appendix
A) proposed by Carnevalli and Miguel (2008) is then adopted for articles classification.Overall, QFD has been confirmed as a useful technique for business to systematically translate customer requirement into available technical requirements, while its application on service recovery is rare. Thus, this study extends the QFD’s balance translating conception into service failure and service recovery issue to fit this research gap.
Table 5
Summary of QFD-based literatures
Author (year) Kind of study (T1) QFD application (T9) QFD advanced methodology
Partovi (2007)
F: a manufacturer in the painting and adhesive products segment of the
chemical industry
A1, A6: for process selection and evaluation for manufacturing systems
[C]The AHP will be used to determine the intensity of the relationship between row and column variables of each matrix, and to evaluate the cost associated with each decision.
[D]The ANP is used to determine the intensity of synergy effects among column variables.
[E]A cost-benefit analysis will be conducted in order to determine the best production strategy.
Wang (2007) E: China Airlines A1: to better prioritize internal service operations
[G]Original QFD is used to assist management in understanding the voice of outside consumer and to better prioritize internal operations.
Iranmanesh and Thomson (2008)
D: a loud speaker (example product)
A2, A3: to assists designers to allocate the correct expenditure on designing in
order to optimize product value
[B]To achieve the customer desired product attributes at minimum cost, a multi-objective programming model is proposed to determine design characteristics.
Yadav and Goel (2008)
A, D: simulation is used to generate the data in
automatic industry
A3, A6: for customer satisfaction driven quality improvement target
planning on vehicle development
[G]QFD and Kano model are included in the product development processes in order to identify and prioritize potential attributes for further.
Chin, Wang, Yang, and
Poon (2009) A, D
A2: to prioritize design requirements with both CRs and customers’
preferences taken into account
[G]An evidential reasoning (ER) based methodology is applied for synthesizing various types of assessment information provided by a group of customers and multiple QFD team members.
Table 5 (con.)
Author (year) Kind of study (T1) QFD application (T9) QFD advanced methodology
Zhang and Chu (2009)
A, F: a horizontal directional drilling
machine
A3: for product development
[C][E]A group decision-making approach incorporating with
“logarithmic least squares model” and “weighted least squares model” is proposed to aggregate the multi-format and multi-granularity linguistic judgments of decision-makers, in which Fuzzy set theory is utilized to address the uncertainty in the decision-making process.
Utne (2009) F: the Norwegian fishing fleet
A6: for fisheries management regarding sustainability/environment,
and for design of fishing vessels
[B][E]Eco-QFD is proposed by extending the scope of QFD, and combining with Life-Cycle Cost and Life-Cycle Analysis to evaluate environmental effects and costs in the system development process.
Ramanathan and Yunfeng (2009)
A, F: the major producers of security
fasteners in China
A3: to develop a more competitive product design
[E]Data envelopment analysis is suggested for deriving the relative importance of design requirements (DRs) when several additional factors (in this study, including cost and environmental impact) are considered.
Liu (2009)
A, F: a small-medium manufacturer in Taiwan
that produce double layered stainless
vacuums
A3: to apply the proposed E-QFD method in the process of designing and
developing the stainless thermos
[E]The original part deployment table is modified by adding “Bottleneck level of PCs” and “RPN value of PCs”; a fuzzy ranking method is applied to determine the bottleneck rankings, and then PCs are classified into several groups through a modified fuzzy clustering method.
Bottani (2009) F A1, A6: to identify the most
appropriate enablers to achieve agility
[A][B]By building two subsequent HoQs, competitive bases, agile attributes and enablers are directly linked.
[C][D]The whole scaffold exploits fuzzy logic to deal with linguistics judgments expressing relationships and correlations required in the HoQ.
Table 5 (con.)
Author (year) Kind of study (T1) QFD application (T9) QFD advanced methodology
Karsak and Özogul (2009)
F: a Turkish automotive parts manufacturer
A7: to develop a novel decision framework for ERP software selection
[A]AHP method is used to determine the relative importance weights of corporation’s requirements.
[C][D]The relationships between corporation requirements and ERP characteristics and among ERP characteristics are determined by fuzzy linear regression.
[E]A weighted zero-one goal programming model is proposed to determine the most suitable ERP system alternative.
Li, Tang, Luo, Yao, and Xu (2010)
A, F: a novel type of two-cylinder washing
machine
A2: to demonstrate the feasibility of the proposed approach
[B]A series of algorithms are proposed for acquiring the set of engineering characteristics used in product planning house of quality.
Li et al. (2010) F: fully automatic washing machine
A2, A3: for mature-period product improvement
[F]A new methodology is proposed to rate the final importance of CRs by the integration of (1) improved maximal deviation approach for dealing with the corporations’ performance estimations, (2) importance rating for CRs by AHP, and (3) importance ratings of achieving the targets of CRs on the basis of Kano model.
Chen and Ko (2010)
F: a semiconductor packing case of the turbo
thermal ball grid array
A2, A3: for new product development with the consideration of MEC concept
[C]Based on the means-end chain (MEC) concept, a set of fuzzy linear programming models are built to determine the contribution levels of each “HOWs” for customer satisfaction.
[E]The risk analysis, FMEA, is incorporated into the QFD process as the constraint in the models.
Table 5 (con.)
Author (year) Kind of study (T1) QFD application (T9) QFD advanced methodology
Lin, Cheng, Tseng, and Tsai (2010)
F: a Taiwanese original equipment manufacturing firm
A1, A6: to get a better understanding of a strategic operating decision area in
improvement of production process toward sustainability
[A][B]The ‘Whats’ question of environmental production requirements (EPRs) and ‘Hows’ problem of the sustainable production indicators (SPIs) are made.
[D]The crisp value of importance with interdependence of EPRs and SPIs are calculated by fuzzy-ANP.
Khademi-Zare, Zarei, Sadeghieh, and Owlia
(2010)
E: Iran mobile telecommunication
A1, A2: to develop the strategic actions to meet the users’ expectations
[A]Model I: Fuzzy-TOPSIS method is applied to prioritize CRs; Model II: AHP method is utilized to prioritize CRs.
[E]The cost and benefit are included in final strategic actions implementation.
Wang, Lin, and Huang (2010)
F: a drug development project in the pharmaceutical industry
A3, A6: to propose a
performance-oriented risk management framework for R&D project
[B]QFD is adapted to transform organizational performance measures into project performance measures.
[E]Utility theory is used to determine R&D risks.
[F]The balanced scorecard is used to identify major performance measures of an R&D organization.
Sener and Karsak (2011)
A, F: a washing machine in Turkish home laundry
appliances industry
A3: to improve product quality and increase customer satisfaction
[C][D]Fuzzy regression is introduced in the model to identify the functional relationships between CNs and ECs, and among ECs. Then considering the multi-objective nature of the product design problem, fuzzy multiple objective programming is included.
Note: [A] represent the modification on WHATs of HoQ; [B] represent the modification on HOWs of HoQ; [C] represent the modification on Relationship Matrix of HoQ;
[D] represent the modification on Correlation Matrix of HoQ; [E] represent the modification on Technical Matrix of HoQ; [F] represent the modification on Competitive bench-marketing Matrix of HoQ; [G] represent the application of the original QFD method.