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 In other words, the assumption is that there is no new need discovered along the time or an old one becomes outdated; only the relative importance change of the existing needs is dealt with.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

A NEW LOGARITHM METHODOLOGY OF ADDITIVE WEIGHTS (LMAW) FOR MULTI-CRITERIA DECISION-MAKING: APPLICATION IN LOGISTICS

Logistics management has been playing a significant role in ensuring competitive growth of industries and nations. This study proposes a new Multi-Criteria Decision-making (MCDM) framework for evaluating operational efficiency of logistics service provider (LSP). We present a case study of comparative analysis of six leading LSPs in India using our proposed framework. We consider three operational metrics such as annual overhead expense (OE), annual fuel consumption (FC) and cost of delay (CoD, two qualitative indicators such as innovativeness (IN) which basically indicates process innovation and average customer rating (CR)and one outcome variable such as turnover (TO) as the criteria for comparative analysis. The result shows that the final ranking is a combined effect of all criteria. However, it is evident that IN largely influences the ranking. We carry out a comparative analysis of the results obtained from our proposed method with that derived by using existing established frameworks. We find that our method provides consistent results; it is more stable and does not suffer from rank reversal problem

An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production

A hybrid model was developed by combining multiple-criteria decision-making (MCDM) with the analytic hierarchy process (AHP) and a fuzzy set to give decision support for choosing sustainable solutions to agricultural problems. Six steps were taken to build the suggested hybrid model: identifying and weighing criteria; normalizing data using fuzzy membership functions; calculating the weighting of the criteria using AHP; and selecting the best alternative for the agricultural problem. The objective of this case study is to demonstrate how agricultural production techniques (APTs) are becoming more complex as agricultural production becomes more complex. Organic agriculture aims to protect both the environment and consumer satisfaction by utilizing organic management practices that do not have the negative effects associated with conventional and genetic engineering production. Meanwhile, products obtained through conventional and genetic engineering techniques are more cost-effective. To present the superiority of the proposed fuzzy MCDM hybrid model, this problem is used as the causative agent’s dataset. Because the challenge involves a large number of competing quantitative and qualitative criteria, the assessment approach should improve the ratio of input data to output data. As a result, agricultural productivity should be controlled holistically. However, because the problem may contain both qualitative and quantitative facts and uncertainties, it is necessary to represent the uncertainty inherent in human thinking. To achieve superior outcomes, fuzzy set theory (FST), which enables the expression of uncertainty in human judgments, can be integrated with). The purpose of this study is to present a novel MCDM approach based on fuzzy numbers for analyzing decision-making scenarios. The proposed methodology, which is based on Buckley’s fuzzy analytic hierarchy process (B-FAHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), uses Buckley’s fuzzy analytic hierarchy process (B-FAHP) and fuzzy TOPSIS to determine weights and rank alternatives, respectively. As a result, we attempted to include both the uncertainty and hesitancy of experts in the decision-making process through the use of fuzzy numbers. We have three main criteria in this study: Satisfaction (C1), Economy (C2), and Environment (C3). An important objective of the current research is to build a complete framework for evaluating and grading the suitability of technologies. A real-world case study is used to demonstrate the suggested paradigm’s validity. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Evaluation of Job Offers Using The Evidential Reasoning Approach

The word 2018;Job2019; term as a regular activity performed in exchange for payment is considered as one of the most important activities for many families worldwide .Evaluation is necessary when more than one opportunity come to an To fulfill their desired goal, it is the 2018;evaluation2019; which assesses among the factors. In addition, it is difficult to measure qualitative factors in a quantitative way, resulting incomplete-ness in data and hence, uncertainty. Besides it is essential to address the subject of uncertainty by using apt methodology; otherwise, the decision to choose a job will become inapt. There exist many methods name as Analytical Hierarchical Process (AHP), Analytical Network Process (ANP) and so on. But the mentioned methods are not suitable to address the subject of uncertainty and hence, resulting inappropriate selection to the expecting job. Therefore, this paper demonstrates the application of a novel method named Evidential Reasoning (ER), which is capable of addressing the uncertainty of multi-criterion problem, where there exist factors of both subjective and objective nature. The ER method handles uncertainties by using a belief structure is aggregating degrees of belief from lower level factors to higher level factors