Optimization of the product design through Quality Function Deployment (QFD) and Analaytical Hierarchy Process (AHP): A case study in a ceramic washbasin

Thesis (Master)--Izmir Institute of Technology, Industrial Design, Izmir, 2009Includes bibliographical references (leaves: 67-79)Text in English; Abstract: Turkish and Englishx, 81 leavesQFD is a methodology, which establishes a relationship between product and customer, determines product.s sales ability and carry out it to a high level during the process.In this study, QFD methodology, which is used in several industries, was implemented in the sanitary production industry. In this purpose, the washbasin, which is called as .Potsink. produced by Vitra, was chosen and examined implementation ability of the methodology. The aim for this choice is that Potsink.s design is different from usual washbasin forms and because of this reason, some sales problems would be appeared also there are some ergonomical and functional problems was observed.In the first step, which is developed by the customer.s voice, Analytic Hierarchy Process AHP was used. The relationship, which is between product and customer.s requirements, is determined by Analytic Hierarchy Process AHP.After this step, with customer requirements and technical details, which is matched with, are put in the house of quality (HoQ). Fallowing this step, improvement ratio and sales points are taken place in the house. Finally calculate all items and evaluated

Smart Product Design Process through the Implementation of a Fuzzy Kano-AHP-DEMATEL-QFD Approach

Product design has become a critical process for the healthcare technology industry, given the ever-changing demands, vague customer requirements, and interrelations among design criteria. This paper proposed a novel integration of fuzzy Kano, Analytic Hierarchy Process (AHP), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Quality Function Deployment (QFD) to translate customer needs into product characteristics and prioritize design alternatives considering interdependence and vagueness. First, the customer requirements were established. Second, the fuzzy KANO was applied to calculate the impact of each requirement, often vague, on customer satisfaction. Third,designalternativesweredefined,whiletherequirements’weightswerecalculated usingAHP.DEMATELwaslaterimplementedforevaluatingtheinterdependenceamongalternatives. Finally,QFDwasemployedtoselectthebestdesign. Ahipreplacementsurgeryaiddeviceforelderly people was used for validation. In this case, collateral issues were the most important requirement, while code change was the best-ranked design

A weighted interval rough number based method to determine relative importance ratings of customer requirements in QFD product planning

Customer requirements (CRs) play a significant role in the product development process, especially in the early design stage. Quality function deployment (QFD), as a useful tool in customer-oriented product development, provides a systematic approach towards satisfying CRs. Customers are heterogeneous and their requirements are often vague, therefore, how to determine the relative importance ratings (RIRs) of CRs and eventually evaluate the final importance ratings is a critical step in the QFD product planning process. Aiming to improve the existing approaches by interpreting various CR preferences more objectively and accurately, this paper proposes a weighted interval rough number method. CRs are rated with interval numbers, rather than a crisp number, which is more flexible to adapt in real life; also, the fusion of customer heterogeneity is addressed by assigning different weights to customers based on several factors. The consistency of RIRs is maintained by the proposed procedures with design rules. A comparative study among fuzzy weighted average method, rough number method and the proposed method is conducted at last. The result shows that the proposed method is more suitable in determining the RIRs of CRs with vague information

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 New Integrated FQFD Approach for Improving Quality and Reliability of Solar Drying Systems

Saffron is the most expensive spice and is significantly valuable in non-oil export. Drying process of saffron is considered as a critical control point with major effects on quality and safety parameters. A suitable drying method covering standards and market requirements while it is costlty benefitial and saves energy is desirable. Solar drying could be introduced as an appropriate procedure in rural and collecting sites of saffron since major micorobial and chemical factors of saffron can be preserved and achieved by using a renewable energy source. So, a precise system taking advantage of management, engineering and food technology sciences could be developed. Since there was no published record of integrated methods of Analytical Hierarchy Process (AHP) and Fuzzy Quality Function Deployment (FQFD) applied to solar energy drying systems, in this paper, Fuzzy Quality Function Deployment as a quality management tool by emphasizing technical and customer requirements has been implemented in order to improve quality parameters, optimizing technological expenses and market expansion strategy. Subsequently, Analytical Hierarchy Process based on survey from customers and logical pair-wise comparison are employed to decrease costs and increase the efficiency and the effectiveness of economic indicators. Using the integrated approach of AHP and FQFD in solar drying systems in saffron industry will result in cost benefit, quality improvement, the customer satisfaction enhancement, and the increase in saffron exports

Applying fuzzy analytic network process in quality function deployment model

In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view

Evaluation of Product Quality in QFD using Multi Attribute Decision Making (MADM) Techniques in Manufacturing Industry

Every customer wants to purchase the best quality product but the price factor is only the reason due to which most of customers compromise with quality. The main purpose of our study is to find a best suitable method which will be helpful to design such product having good quality with affordable price. Quality Function Deployment (QFD) is the most powerful method for analyzing the customer demands and selection of most important or valuable voice which has to be corrected or modified. The integrated approach of QFD and Optimization techniques (i.e. AHP, TOPSIS, PROMETHEE, etc.) can be used to analyze the product quality manufacturing industry. A QFD optimization methodology is formulated in this study with suitable illustrations and tried to find a best method of product design. Keywords: Quality Function Deployment, PROMETHEE, AHP, TOPSIS, House of Quality

Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

Designing complex engineering systems, such as an aircraft or an aero-engine, is immensely challenging. Formal Systems Engineering (SE) practices are widely used in the aerospace industry throughout the overall design process to minimise the overall design effort, corrective re-work, and ultimately overall development and manufacturing costs. Incorporating the needs and requirements from customers and other stakeholders into the conceptual and early design process is vital for the success and viability of any development programme. This paper presents a formal methodology, the Value-Driven Design (VDD) methodology that has been developed for collaborative and iterative use in the Extended Enterprise (EE) within the aerospace industry, and that has been applied using the Concept Design Analysis (CODA) method to map captured Customer Needs (CNs) into Engineering Characteristics (ECs) and to model an overall ‘design merit’ metric to be used in design assessments, sensitivity analyses, and engineering design optimisation studies. Two different case studies with increasing complexity are presented to elucidate the application areas of the CODA method in the context of the VDD methodology for the EE within the aerospace secto

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