Manufacturing Quality Function Deployment: Literature Review and Future Trends

A comprehensive review of the Quality Function Deployment (QFD) literature is made using extensive survey as a methodology. The most important results of the study are: (i) QFD modelling and applications are one-sided; prioritisation of technical attributes only maximise customer satisfaction without considering cost incurred (ii) we are still missing considerable knowledge about neural networks for predicting improvement measures in customer satisfaction (iii) further exploration of the subsequent phases (process planning and production planning) of QFD is needed (iv) more decision support systems are needed to automate QFD (v) feedbacks from customers are not accounted for in current studies

A fuzzy-QFD approach for the enhancement of work equipment safety: a case study in the agriculture sector

The paper proposes a design for safety methodology based on the use of the Quality Function Deployment (QFD) method, focusing on the need to identify and analyse risks related to a working task in an effective manner, i.e. considering the specific work activities related to such a task. To reduce the drawbacks of subjectivity while augmenting the consistency of judgements, the QFD was augmented by both the Delphi method and the fuzzy logic approach. To verify such an approach, it was implemented through a case study in the agricultural sector. While the proposed approach needs to be validated through further studies in different contexts, its positive results in performing hazard analysis and risk assessment in a comprehensive and thorough manner can contribute practically to the scientific knowledge on the application of QFD in design for safety activities

SIMULATION-BASED DECISION MODEL TO CONTROL DYNAMIC MANUFACTURING REQUIREMENTS: APPLICATION OF GREY FORECASTING - DQFD

Manufacturing systems have to adapt to changing requirements of their internal and external customers. In fact, new requirements may appear unexpectedly and may change multiple times. Change is a straightforward reality of production, and the engineer has to deal with the dynamic work environment. In this perspective, this paper proposes a decision model in order to fit actual and future processes’ needs. The proposed model is based on the dynamic quality function deployment (DQFD), grey forecasting model GM (1,1) and the technique for order preference by similarity to ideal solution (TOPSIS). The cascading QFD-based model is used to show the applicability of the proposed methodology. The simulation results illustrate the effect of the manufacturing needs changes on the strategic, operational and technical improvements

Three Decades of Fuzzy AHP: A Bibliometric Analysis

[EN] For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the field¿s agenda to advise the editors of high-impact journals on gaps and new research trends.Castello-Sirvent, F.; Meneses-Eraso, C.; Alonso-Gómez, J.; Peris-Ortiz, M. (2022). Three Decades of Fuzzy AHP: A Bibliometric Analysis. Axioms. 11(10):1-34. https://doi.org/10.3390/axioms11100525134111

Bibliometric analysis of quality function deployment with fuzzy systems

Research on quality function deployment (QFD) with fuzzy systems has increased since the 2000s. The growing number of QFD applications with fuzzy systems indicates worldwide attention on this field of research. Then, two research questions arise: Are there some trends? And, are there some research gaps? This paper presents bibliometric analysis to answer those questions, performed on data from Scopus database, in a total output of 598 documents. Only articles and reviews were searched. China is the leading country in publication and international collaboration (207 published documents, more than a third of total). The main finding of analysis is the trend of QFD integration with fuzzy and multi-criteria decision-making (MCDM) methods. This could be observed with different applications as new product development, quality management, service quality, and supply chain management, to name a few.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(undefined

Some further studies on improving QFD methodology and analysis

Quality Function Deployment (QFD) starts and ends with the customer. In other words, how it ends may depend largely on how it starts. Any QFD practitioners will start with collecting the voice of the customer that reflects customer’s needs as to make sure that the products will eventually sell or the service may satisfy the customer. On the basis of those needs, a product or service creation process is initiated. It always takes a certain period of time for the product or service to be ready for the customer. The question here is whether those customer-needs may remain exactly the same during the product or service creation process. The answer would be very likely to be a ‘no’, especially in today’s rapidly changing environment due to increased competition and globalization. The focus of this thesis is placed on dealing with the change of relative importance of the customer’s needs during product or service creation process. In other words, the assumption is that there is no new need discovered along the time or an old one becomes outdated; only the relative importance change of the existing needs is dealt with. Considering the latest development of QFD research, especially the increasingly extensive use of Analytic Hierarchy Process (AHP) in QFD, this thesis aims to enhance the current QFD methodology and analysis, with respect to the change during product or service creation process, as to continually meet or exceed the needs of the customer. The entire research works are divided into three main parts, namely, the further use of AHP in QFD, the incorporation of AHP-based priorities’ dynamics in QFD, and decision making analysis with respect to the dynamics. The first part focuses on the question "In what ways does AHP, considering its strength and weakness, contribute to an improved QFD analysis?" The usefulness of AHP in QFD is demonstrated through a case study in improving higher education quality of an education institution. Furthermore, a generalized model of using AHP in QFD is also proposed. The generalized model not only provides an alternative way to construct the house of quality (HoQ), but also creates the possibility to include other relevant factors into QFD analysis, such as new product development risks. The second part addresses the question "How to use the AHP in QFD in dealing with the dynamics of priorities?" A novel quantitative method to model the dynamics of AHP-based priorities in the HoQ is proposed. The method is simple and time-efficient. It is especially useful when the historical data is limited, which is the case in a highly dynamic environment. As to further improve QFD analysis, the modeling method is applied into two areas. The first area is to enhance the use of Kano’s model in QFD by considering its dynamics. It not only extends the use of Kano’s model in QFD, but also advances the academic literature on modeling the life cycle of quality attributes quantitatively. The second area is to enhance the benchmarking part of QFD by including the dynamics of competitors’ performance in addition to the dynamics of customer’s needs. The third part deals with the question "How to make decision in a QFD analysis with respect to the dynamics in the house of quality?" Two decision making approaches are proposed to prioritize and/or optimize the technical attributes with respect to the modeling results. Considering the fact that almost all QFD translation process employs the relationship matrix, a guideline for QFD practitioners to decide whether the relationship matrix should be normalized is developed. Furthermore, a practical implication of the research work towards the possible use of QFD in helping a company develop more innovative products is also discussed. In brief, the main contribution of this thesis is in providing some novel methods and/or approaches to enhance the QFD’s use with respect to the change during product or service creation process. For scientific community, this means that the existing QFD research has been considerably improved, especially with the use of AHP in QFD. For engineering practice, a better way of doing QFD analysis, as a customer-driven engineering design tool, has been proposed. It is hoped that the research work may provide a first step into a better customer-driven product or service design process, and eventually increase the possibility to create more innovative and competitive products or services over time

Risk Prioritization using A FUZZY BASED Approach in Software Development Design Phase

The success of a software project's objective is directly proportional to the degree to which it satisfies all of the stakeholders' concerns regarding the project's requirements, including the budget, schedule, and overall performance. Risks can occur throughout the software development lifecycle (SDLC) phases and affect every phase. The design phase of the SDLC yields an overview of the software and can be defined as the software's blueprint. Different types of software have their own unique design phases and have different types of risks. With the high number of interacting components, complex systems have a greater propensity to be more volatile, which increases the risk. It is necessary to prioritize the risks in order of their severity levels. The issue at hand is the lack of effective methods to prioritize and mitigate the risk. Recent studies have suggested several methods for prioritizing risks, but it is clear that few of these have been implemented. These methods are overly complicated, time-consuming, prone to inconsistency, and challenging to put into practice. This paper proposes a novel Fuzzy-based approach to risk prioritization in the software design phase using MATLAB software. Fuzzy-based models have been shown to be more accurate than other techniques when using standard datasets to prioritize risks. Fuzzy-based methods that have been proposed take into account the characteristics of risks by modelling those characteristics as fuzz