Combining Quality Function Deployment Research Articles

Application of Quality Function Deployment for Product Design Concept Selection

For business-to-business (B2B) companies, selecting new product concepts is vital to new product development (NPD), since it significantly contributes to the ultimate success and reputation of the product in terms of quality and function. The research problem is defining the best solution of new product’s design concept selection within high competition and resources’ limitation by mathematical approaches. The main objective of this study is developing an integrated analytical approach, combining quality function deployment (QFD) and analytic hierarchy process (AHP) approach, and data envelopment analysis (DEA) to enhance the effectiveness of design product decisions. The proposed approach focuses on mathematical methods to comprehensively evaluate and strategically select the best new product concept while considering the features of the B2B product and the available information during concept selection. The best new concept is selected by the combined scores derived from the concept competitiveness (quality function deployment—analytic hierarchy process) and the design development efficiency (data envelopment analysis). Finally, the design alternatives are classified into four categories by quadrant analysis for design concept management. The benefit of this approach—combining three mathematical models together for the best concept’s solution.

Supplier selection using hybrid multicriteria decision-making methods

PurposeThe paper develops a decision-making model for supplier selection combining quality function deployment (QFD), analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The efficacy of the model was demonstrated by applying it for supplier selection of lithium ion batteries.Design/methodology/approachThe proposed methodology involved identifying customer requirements for lithium ion batteries and translating them to requisite technical characteristics using QFD. Further, separate sourcing, safety and sustainability-related supplier parameters were proposed taking into account the manufacturer's point of view. The relative weight of each parameter was then calculated using AHP, and finally, TOPSIS was used to select the best supplier.FindingsThe proposed methodology was applied to six suppliers of lithium ion batteries, and the obtained results were used to select the most and least preferred suppliers.Practical implicationsThe obtained results cannot be generalized and are valid to the case environment. However, the proposed approach can be used for any environment related to supplier selection after capturing the corresponding parameters. The proposed approach does not restrict the number of parameters to be considered.Originality/valueMany researches related to supplier evaluation are reported in literature, but few studies are available related to supplier performance evaluation for lithium ion batteries using QFD, AHP and TOPSIS. The study will provide a guideline for comparing and selecting supplier on the basis of performance in general and its application to lithium ion batteries in specific.

A Combined Quality Function Deployment Approach for Determining the Quality Characteristics of Undergraduate Programs

In this study, a combined approach of Quality Function Deployment (QFD) and the Exploratory Factor Analysis (EFA) has been used to extract and to determine the important quality characteristics of undergraduate programs. We have required to take advantage of the exploratory factor analysis as a data/dimension reduction tool in order to improve the effectiveness of QFD, because of a great number of customer requirements. 10 latent factors (Academic Staff (AS), Physical Facilities (PF), Career Prospects (CP), The Competence of Canteen Facility (CCF), Scientific Research Activities (SRA), Campus Design (CD), Club Activities (CA), Social Environment (SE), Physical Environment-Interior (PEI) and Adequate Library Services (ALS)) as students' requirements were determined after the implementation of EFA. The house of quality was constructed on basis of those 10 factors. Consequently, the findings are going to provide insights and sentiments to researchers and managers in higher education system.

Combining quality function deployment with simple additive weighting for interval-valued fuzzy multi-criteria decision-making with dependent evaluation criteria

In the past, lots of multi-criteria decision-making (MCDM) methods included simple additive weighting (SAW) extended under fuzzy environment into multi-criteria decision-making (FMCDM) methods to encompass uncertainty and vagueness of data. The extensions were first used in FMCDM with independent evaluation criteria, and then, FMCDM could be associated with quality function deployment (QFD) to break the tie of dependent evaluation criteria. Commonly, alternative ratings and criteria weights in FMCDM were expressed by general fuzzy numbers (i.e., triangular or trapezoidal fuzzy numbers). Recently, some approaches proposed FMCDM with independent evaluation criteria under interval-valued fuzzy environment. For interval-valued fuzzy numbers, FMCDM with dependent evaluation criteria was scarcely elaborated due to computation complexity. Besides, QFD was also generalized under some fuzzy environments consisting of triangular fuzzy numbers or trapezoidal fuzzy numbers, but not interval-valued fuzzy environment. Practically, interval-valued fuzzy numbers are deemed as a kind of fuzzy number that can grasp more information than other fuzzy numbers, but the kind of fuzzy number is more complex on computation than others. Based on above, we desire to extend QFD and SAW under interval-valued fuzzy environment for FMCDM with dependent evaluation criteria. By a rational technique of combining QFD with SAW under fuzzy environment, the computation tie of interval-valued fuzzy numbers corresponding to dependent evaluation criteria is resolved, and more messages are grasped than using other fuzzy numbers in FMCDM.

Fault correlation analysis-based framework for reliability deployment of electromechanical system

Reliability allocation is a very critical step of product development process for setting achievable reliability goals. However, most research on reliability allocation have ignored the correlation between faults in a complex electromechanical system. In view of this problem, this work proposed an optimizationmethod of reliability allocation by combining Quality Function Deployment (QFD) and Failure Tree Analysis (FTA). First, a fault tree of the system is build, and failure mode of the system is discovered in the bottom events of the fault tree. Second, the failure mode in previous step is input into House of Reliability (HoR), and the correlation of faults and fault severity could be calculated in the HoR. Finally, according to the results of HoR, the fault severity of each component is transformed into the importance degree, and the system reliability target is allocated to each component on the basis of the importance degree. A case study of a transmission agent was conducted to illustrate the analysis and application processes of the proposed method. The result showed that this method made the distribution more reasonable by considered the correlation between failures.

Novel green supplier selection method by combining quality function deployment with partitioned Bonferroni mean operator in interval type-2 fuzzy environment

Green supplier selection (GSS) plays a significant role in promoting enterprise development. Quality function deployment (QFD) ensures that green supplier assessment criteria are in accordance with the characteristics that purchased products ought to possess. The partitioned Bonferroni mean (PBM) operator assumes that all criteria are partitioned into several clusters, where criteria in the same clusters are interrelated, while criteria in different clusters are irrelevant, and it can be used to deal with GSS problems in which all criteria are partitioned into several clusters. Furthermore, interval type-2 fuzzy sets (IT2FSs) can efficiently express vagueness and imprecision, and possess powerful processing abilities. In this paper, we propose a novel GSS method by combining QFD with the PBM operator in the context of IT2FSs. Firstly, we present the interval type-2 fuzzy PBM (IT2FPBM) operator and interval type-2 fuzzy weighted PBM (IT2FWPBM) operator, and discuss several of their properties. Thereafter, we transform the preference values of the importance degrees of customer needs (CNs) into those of technical criteria (TC) through the relationships between CNs and TC, based on QFD. Moreover, the criteria are partitioned on the basis of the literature review on GSS criteria. Finally, a bike-share case is used to illustrate the applicability of the presented method, and various comparisons are used to display the superiority of the presented method.

Integrating Kano’s Model into Quality Function Deployment for Product Design: A Comprehensive Review

Many methods and techniques are adopted by some companies to improve the competitiveness through the fulfillment of customer satisfaction by enhancement and improvement the product design quality. Over the past few years, several researcher have studied extensively combining Quality Function Deployment and Kano’s model as design techniques by focusing on translating consumer desires into a product design. This paper presents a review and analysis of several literatures that associated to the integration methodology of Kano into the QFD process. Various of international journal articles were selected, collected and analyzed through a number of relevant scientific publications. In-depth analysis was performed, and focused in this paper on the results, advantages and drawbacks of its methodology. In addition, this paper also provides the analysis that acquired in this study related to the development of the methodology. It is hopedd this paper can be a reference for other researchers and manufacturing companies to implement the integration method of QFD- Kano for product design.

An alternative fuzzy evaluation framework for supplier selection

Organisations need for an effective supplier selection system towards attaining the competition advantages in the market. In this paper, we propose an alternative supplier selection framework integrated by fuzzy c-means, belief-based quality function deployment, fuzzy weighted average, and a proposed fuzzy decision measure. This framework consists of three phases. In the first phase, we present the potential assessments for a supplier selection and their uncertainty descriptions. We divide supplier assessments into two parts: 1) expert assessments using combined belief-based quality function deployment and fuzzy weighted average; 2) system assessments comprised of a multi input-single output system. In the second phase, we analyse uncertainties of both expert and current systems using the well-known fuzzy c-means. In the third phase, we propose a fuzzy decision measure to complete the supplier selection procedure with finding the most appropriate supplier. We apply this framework to supplier selection process of a Turkish Machinery Corporation.

Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach

The business performance of manufacturing organizations depends on the reliability and productivity of equipment, machineries and entire manufacturing system. Therefore, the main role of maintenance and production managers is to keep manufacturing system always up by adopting most appropriate maintenance methods. There are alternative maintenance techniques for each machine, the selection of which depend on multiple factors. The contemporary approaches to maintenance technique selection emphasize on operational needs and economic factors only. As the reliability of production systems is the strategic intent of manufacturing organizations, maintenance technique selection must consider strategic factors of the concerned organization along with operational and economic criteria. The main aim of this research is to develop a method for selecting the most appropriate maintenance technique for manufacturing industry with the consideration of strategic, planning and operational criteria through involvement of relevant stakeholders. The proposed method combines quality function deployment (QFD), the analytic hierarchy process (AHP) and the benefit of doubt (BoD) approach. QFD links strategic intents of the organizations with the planning and operational needs, the AHP helps in prioritizing the criteria for selection and ranking the alternative maintenance techniques, and the BoD approach facilitates analysing robustness of the method through sensitivity analysis through setting the realistic limits for decision making. The proposed method has been applied to maintenance technique selection problems of three productive systems of a gear manufacturing organization in India to demonstrate its effectiveness.

Combined quality function deployment and logical framework analysis to improve quality of emergency care in Malta.

The purpose of this paper is to develop an integrated patient-focused analytical framework to improve quality of care in accident and emergency (A & E) unit of a Maltese hospital. The study adopts a case study approach. First, a thorough literature review has been undertaken to study the various methods of healthcare quality management. Second, a healthcare quality management framework is developed using combined quality function deployment (QFD) and logical framework approach (LFA). Third, the proposed framework is applied to a Maltese hospital to demonstrate its effectiveness. The proposed framework has six steps, commencing with identifying patients' requirements and concluding with implementing improvement projects. All the steps have been undertaken with the involvement of the concerned stakeholders in the A & E unit of the hospital. The major and related problems being faced by the hospital under study were overcrowding at A & E and shortage of beds, respectively. The combined framework ensures better A & E services and patient flow. QFD identifies and analyses the issues and challenges of A & E and LFA helps develop project plans for healthcare quality improvement. The important outcomes of implementing the proposed quality improvement programme are fewer hospital admissions, faster patient flow, expert triage and shorter waiting times at the A & E unit. Increased emergency consultant cover and faster first significant medical encounter were required to start addressing the problems effectively. Overall, the combined QFD and LFA method is effective to address quality of care in A & E unit. PRACTICAL/IMPLICATIONS: The proposed framework can be easily integrated within any healthcare unit, as well as within entire healthcare systems, due to its flexible and user-friendly approach. It could be part of Six Sigma and other quality initiatives. Although QFD has been extensively deployed in healthcare setup to improve quality of care, very little has been researched on combining QFD and LFA in order to identify issues, prioritise them, derive improvement measures and implement improvement projects. Additionally, there is no research on QFD application in A & E. This paper bridges these gaps. Moreover, very little has been written on the Maltese health care system. Therefore, this study contributes demonstration of quality of emergency care in Malta.

Optimal selection of third-party logistics service providers using quality function deployment and Taguchi loss function

Purpose – Selection of logistics service provider (LSP) (also known as Third-party logistics (3PL) is a critical decision, because logistics affects top and bottom line as well. Companies consider logistics as a cost driver and at the time of LSP selection decision, many important decision criteria’s are left out. 3PL selection is multi-criteria decision-making process. The purpose of this paper is to develop an integrated approach, combining quality function deployment (QFD), and Taguchi loss function (TLF) to select optimal 3PL. Design/methodology/approach – Multiple criteria are derived from the company requirements using house of quality. The 3PL service attributes are developed using QFD and the relative importance of the attributes are assessed. TLFs are used to measure performance of each 3PL on each decision variable. Composite weighted loss scores are used to rank 3PLs. Findings – QFD is a better tool which connects attributes used in a decision problem to decision maker’s requirements. In total, 15 criteria were used and TLF provides performance on these criteria. Practical implications – The proposed model provides a methodology to make informed decision related to 3PL selection. The proposed model may be converted into decision support system. Originality/value – Proposed approach in this paper is a novel approach that connects the 3PL selection problem to practice in terms of identifying criteria’s and provides a single numerical value in terms of Taghui loss.

Designing a sustainable maritime supply chain: A hybrid QFD–ANP approach

This study aims to design a sustainable maritime supply chain by taking customer requirements as the focus. This is achieved by an analytical approach combining Quality Function Deployment (QFD) and Analytical Network Process (ANP) for guiding shipping companies’ design. An analysis of a major container shipping line is conducted to illustrate and validate the approach. The four main customer requirements are: (1) Cost and Price Competitive, (2) Pollution Reduction, (3) Efficient Use of Fuel and Resources, and (4) Health, Safety, and Security. The Use of Green Design Ships, Engines and Machinery is found to be the most important design requirement.

A new MCDM method combining QFD with TOPSIS for knowledge management system selection from the user's perspective in intuitionistic fuzzy environment

Knowledge management system (KMS) is crucial for organization knowledge management. In order to help the evaluation and selection of KMS from the user's perspective, a new multiple criteria decision making (MCDM) method combining quality function deployment (QFD) with technique for order preference by similarity to an ideal solution (TOPSIS) in intuitionistic fuzzy environment is proposed. In the method, the customer criteria and system criteria for KMS selection are required. These two kinds of criteria are established from the user's perspective and the designer's perspective respectively. Customers give their linguistic opinions about the importance of the customer criteria and the rating of alternatives with respect to the customer criterion. Analysts give their linguistic opinions about the relationship between the customer criteria and the system criteria, and the correlation between the system criteria. After the aggregation of linguistic opinions in intuitionistic fuzzy environment, the customers’ opinions are transformed into the rating of the weight of system criteria and rating of the alternatives concerning the system criteria by the QFD. Afterwards the alternatives are ranked according to system criteria by TOPSIS method in intuitionistic fuzzy environment and the best alternative is determined. In the end an example is provided to illustrate the applicability of the proposed method.

Part Deployment Model using Combined Quality Function Deployment and Cybernetic Fuzzy Analytic Network Process

Quality Function Deployment (QFD) is a customer oriented design tool used to ensure that customer expectations are satisfied in the early design stage. Customers directly and companies indirectly enjoy the benefits of implementing such methodology. Many extensions have been proposed in order to extend QFD’s application or improve limitation of traditional QFD; among which incorporation of Multi–Criteria Decision Making (MCDM) theories into QFD, in particular Analytic Network Process (ANP) is noteworthy. This paper proposes a new extension of QFD called Fuzzy Cybernetic ANP (FCANP) which is able to model QFD tables, especially when company’s experts deal with a large number of customer demands, while subjectivity of judgments are handled. Keywords: Fuzzy Cybernetic Analytic Network Process (FCANP), Part Deployment, Quality Function Deployment (QFD)

Part Deployment Model Using Combined Quality Function Deployment and Cybernetic Fuzzy Analytic Network Process

Quality Function Deployment (QFD) is a customer oriented design tool used to ensure that customer expectations are satisfied in the early design stage. Customers directly and companies indirectly enjoy the benefits of implementing such methodology. Many extensions have been proposed in order to extend QFD's application or improve limitation of traditional QFD; among which incorporation of Multi-Criteria Decision Making (MCDM) theories into QFD, in particular Analytic Network Process (ANP) is noteworthy. This paper proposes a new extension of QFD called Fuzzy Cybernetic ANP (FCANP) which is able to model QFD tables, especially when company's experts deal with a large number of customer demands, while subjectivity of judgments are handled.

Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach

This paper develops an integrated approach, combining quality function deployment (QFD), fuzzy set theory, and analytic hierarchy process (AHP) approach, to evaluate and select the optimal third-party logistics service providers (3PLs). In the approach, multiple evaluating criteria are derived from the requirements of company stakeholders using a series of house of quality (HOQ). The importance of evaluating criteria is prioritized with respect to the degree of achieving the stakeholder requirements using fuzzy AHP. Based on the ranked criteria, alternative 3PLs are evaluated and compared with each other using fuzzy AHP again to make an optimal selection. The effectiveness of proposed approach is demonstrated by applying it to a Hong Kong based enterprise that supplies hard disk components. The proposed integrated approach outperforms the existing approaches because the outsourcing strategy and 3PLs selection are derived from the corporate/business strategy.

Six Sigma project selection via quality function deployment

Six Sigma is one of the most widely used methodologies in many organisations for improving the quality of process/product to enhance customer satisfaction and company revenue. A detailed literature review discloses that the project selection is an area of extreme importance for assuring the success of Six Sigma implementation, but that has been less researched in the past. This research paper aims to develop a project selection method by combining quality function deployment and Six Sigma to assist the organisations as well as Six Sigma consultants for selecting right project. A real-time case study from an Indian small- and medium-sized enterprise is explored in this paper to see the sights of the proposed methodology.

Strategic sourcing: a combined QFD and AHP approach in manufacturing

PurposeThis paper aims to develop an integrated analytical approach, combining quality function deployment (QFD) and analytic hierarchy process (AHP) approach, to enhance the effectiveness of sourcing decisions.Design/methodology/approachIn the approach, QFD is used to translate the company stakeholder requirements into multiple evaluating factors for supplier selection, which are used to benchmark the suppliers. AHP is used to determine the importance of evaluating factors and preference of each supplier with respect to each selection criterion.FindingsThe effectiveness of the proposed approach is demonstrated by applying it to a UK‐based automobile manufacturing company. With QFD, the evaluating factors are related to the strategic intent of the company through the involvement of concerned stakeholders. This ensures successful strategic sourcing. The application of AHP ensures consistent supplier performance measurement using benchmarking approach.Research limitations/implicationsThe proposed integrated approach can be principally adopted in other decision‐making scenarios for effective management of the supply chain.Practical implicationsThe proposed integrated approach can be used as a group‐based decision support system for supplier selection, in which all relevant stakeholders are involved to identify various quantitative and qualitative evaluating criteria, and their importance.Originality/valueVarious approaches that can deal with multiple and conflicting criteria have been adopted for the supplier selection. However, they fail to consider the impact of business objectives and the requirements of company stakeholders in the identification of evaluating criteria for strategic supplier selection. The proposed integrated approach outranks the conventional approaches to supplier selection and supplier performance measurement because the sourcing strategy and supplier selection are derived from the corporate/business strategy.

A combined QFD and integer programming framework to determine attribute levels for conjoint study

Conjoint Analysis (CA) and Quality Function Deployment (QFD) are two popular tools for new product design; marketers frequently use the former and engineers the latter. Typically, in a conjoint study, the attributes and their levels are determined through focus group discussions or market surveys. Sometimes, the market researchers exclude some critical features or include unrealistic attribute levels resulting in infeasible product profiles. Inappropriate selection of attribute levels may render the conjoint study less useful. In QFD, the New Product Development team attempts to identify the technical characteristics (TCs) to be improved (included) to meet the customer requirements (CRs) through a subjective relationship matrix between CRs and TCs. At present there is no methodology that uses the output of QFD to generate feasible product profiles to be used in CA and therefore improve its usefulness. In this paper, QFD is used along with an integer programming (IP) model to determine the appropriate TCs and consequently the right attribute levels. These attribute levels are then used in a conjoint study. It is also proposed to measure the elements of the so-called relationship matrix in QFD in a way so that the right levels of the attributes can be generated from the IP solution. The proposed method is illustrated through a commercial vehicle design problem with hypothetical data. **Atanu Chaudhuri was a doctoral student at Indian Institute of Management, Lucknow, India when this work was carried out.

A hybrid rough-cut process planning for quality

This paper proposes a hybrid approach to develop a rough-cut process planning for quality. The approach aims to determine key process alternatives with an adequate process capability by systematic quality planning and assessment methods during the initial planning stage of the product development cycle. It consists of four steps: (1) identification of quality characteristics (2) planning of the process quality by combining quality function deployment (QFD) with the process failure mode and effect analysis (FMEA) (3) a selection of process alternatives, and (4) an assessment of process quality through a quality measure index, called the composite process capability (CCP). The process alternatives with an adequate CCP selected during the early design stage can then be not only used as the guidelines for detailed process planning but also as feedback for the product design and other functions for design evaluation and improvement. This approach is helpful to reduce or even eliminate the iterations of modification of process plans. A prototype system called the rough-cut process planning for quality (RPPFQ) has been developed for validation. A case study concerned with a satellite frame part is presented to illustrate the approach and prototype system in this paper.