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A QFD-MCDM Approach Considering Kano Model Under Uncertainty, Case Study: Automotive Industry in Portugal = = Uma Abordagem QFD-MCDM Considerando o Modelo Kano Sob Incerteza, Estudo de Caso: Industria Automovel em Portugal /

Record Type:	Electronic resources : Monograph/item
Title/Author:	A QFD-MCDM Approach Considering Kano Model Under Uncertainty, Case Study: Automotive Industry in Portugal =/ Ahmad Hariri.
Reminder of title:	Uma Abordagem QFD-MCDM Considerando o Modelo Kano Sob Incerteza, Estudo de Caso: Industria Automovel em Portugal /
Author:	Hariri, Ahmad,
Description:	1 electronic resource (200 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: A.
Contained By:	Dissertations Abstracts International86-03A.
Subject:	Sustainability. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31472534
ISBN:	9798384364887

A QFD-MCDM Approach Considering Kano Model Under Uncertainty, Case Study: Automotive Industry in Portugal = = Uma Abordagem QFD-MCDM Considerando o Modelo Kano Sob Incerteza, Estudo de Caso: Industria Automovel em Portugal /
Hariri, Ahmad,

A QFD-MCDM Approach Considering Kano Model Under Uncertainty, Case Study: Automotive Industry in Portugal =Uma Abordagem QFD-MCDM Considerando o Modelo Kano Sob Incerteza, Estudo de Caso: Industria Automovel em Portugal /Ahmad Hariri. - 1 electronic resource (200 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: A.

In today's competitive market, most companies aim to improve the quality of their products to acquire new customers and to avoid customer churn. Quality Function Deployment (QFD) is a customer-oriented design tool that aims to meet customer needs in a better way and enhance organizational capabilities, while maximizing company goals. The premise that customer satisfaction is a crucial factor that significantly impacts the outcomes of a business, whether successful or unsuccessful, holds significant weight. Hence, it is important to determine those requirements of a product or service that bring more satisfaction than others. QFD and the Kano model can be integrated effectively to identify customer needs more specifically and yield maximum customer satisfaction. This study proposes an improved refined Kano method for identifying and prioritizing customer requirements (CRs) and engineering characteristics (ECs) called supplier attributes (SAs) in this study-integrated into multi-criteria decision-making (MCDM)- QFD process. This model uses fuzzy theory to rank the suppliers, aiming to enhance black uniformity (BU) as a luminance characteristic on the display surface, by evaluating the CRs and developing the SAs related to CRs.The main findings of this study were the identification, classification, and ranking of the CRs of a product in an automotive company due to classifying the SAs to satisfy these CRs, and finally, the ranking of the suppliers. As the initial stage of QFD, converting CRs into ECs and determining the technical importance of ECs are the foundation for the successful implementation of the QFD tool. However, as indicated by many researchers, there exist various shortcomings in conventional QFD, which limit its efficiency and potential applications. The first concern that exists in conventional QFD is quantifying the relationships between CRs and ECs based on crisp (exact) numbers. Obviously, in practical situations, it is often hard for experts to provide their opinions by using exact values due to environmental complexity and limited experience. The second concern refers to the determination of the CRs' weights based on customers' evaluations without having a structured pair-wise comparison among CRs. Moreover, ignoring decisionmakers' preference behavior by using a linear aggregation method in the traditional QFD could be considered as the third concern. On the other hand, determining the crucial ECs in QFD is often regarded as a MCDM problem. To fill this gap of data uncertainty, the current thesis aimed to integrate the Kano model, QFD, and MCDM procedures into a hybrid methodology.

English

ISBN: 9798384364887Subjects--Topical Terms:

1029978
Sustainability.

A QFD-MCDM Approach Considering Kano Model Under Uncertainty, Case Study: Automotive Industry in Portugal = = Uma Abordagem QFD-MCDM Considerando o Modelo Kano Sob Incerteza, Estudo de Caso: Industria Automovel em Portugal /
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500 $a Advisors: Domingues, Jose Pedro Teixeira; Sampaio, Paulo.
502 $b Ph.D. $c Universidade do Minho (Portugal) $d 2024.
520 $a In today's competitive market, most companies aim to improve the quality of their products to acquire new customers and to avoid customer churn. Quality Function Deployment (QFD) is a customer-oriented design tool that aims to meet customer needs in a better way and enhance organizational capabilities, while maximizing company goals. The premise that customer satisfaction is a crucial factor that significantly impacts the outcomes of a business, whether successful or unsuccessful, holds significant weight. Hence, it is important to determine those requirements of a product or service that bring more satisfaction than others. QFD and the Kano model can be integrated effectively to identify customer needs more specifically and yield maximum customer satisfaction. This study proposes an improved refined Kano method for identifying and prioritizing customer requirements (CRs) and engineering characteristics (ECs) called supplier attributes (SAs) in this study-integrated into multi-criteria decision-making (MCDM)- QFD process. This model uses fuzzy theory to rank the suppliers, aiming to enhance black uniformity (BU) as a luminance characteristic on the display surface, by evaluating the CRs and developing the SAs related to CRs.The main findings of this study were the identification, classification, and ranking of the CRs of a product in an automotive company due to classifying the SAs to satisfy these CRs, and finally, the ranking of the suppliers. As the initial stage of QFD, converting CRs into ECs and determining the technical importance of ECs are the foundation for the successful implementation of the QFD tool. However, as indicated by many researchers, there exist various shortcomings in conventional QFD, which limit its efficiency and potential applications. The first concern that exists in conventional QFD is quantifying the relationships between CRs and ECs based on crisp (exact) numbers. Obviously, in practical situations, it is often hard for experts to provide their opinions by using exact values due to environmental complexity and limited experience. The second concern refers to the determination of the CRs' weights based on customers' evaluations without having a structured pair-wise comparison among CRs. Moreover, ignoring decisionmakers' preference behavior by using a linear aggregation method in the traditional QFD could be considered as the third concern. On the other hand, determining the crucial ECs in QFD is often regarded as a MCDM problem. To fill this gap of data uncertainty, the current thesis aimed to integrate the Kano model, QFD, and MCDM procedures into a hybrid methodology.
520 $a No mercado competitivo de hoje, as empresas tem como objetivo a qualidade e a competitividade dos seus produtos e servicos para captar e reter clientes. Desdobramento da Funcao Qualidade (QFD) e uma ferramenta de design orientada para o cliente, que visa atender melhor as necessidades deste e aprimorar as capacidades organizacionais, maximizando os objetivos da empresa. A premissa de que a satisfacao do cliente e um fator crucial que impacta significativamente os resultados de um negocio, seja bem ou malsucedido, tem um peso significativo. E expectavel que existam alguns requisitos que trazem mais satisfacao ao cliente do que outros. Portanto, e importante determinar os requisitos de um produto ou servico que trazem mais satisfacao do que outros. O QFD e o modelo Kano podem ser integrados efetivamente para identificar as necessidades do cliente de uma forma mais especifica e obter a maxima satisfacao do cliente. Ao utilizar o modelo Kano e integra-lo ao QFD, a equipa de projeto pode entender melhor as necessidades dos clientes, focando adequadamente nelas.Este estudo propoe um modelo Kano refinado para identificar e priorizar os requisitos do cliente (CRs) e identificar as caracteristicas de engenharia (ECs) (atributos do fornecedor (SAs) neste estudo) integrado a uma tomada de decisao multicriterio (MCDM)-QFD considerando a teoria difusa para classificar os fornecedores devido a melhoria da uniformidade do preto (BU) como uma caracteristica de luminancia na superficie de uma tela, avaliando os CRs e desenvolvendo os SAs relacionados aos CRs. Os principais resultados deste estudo foram a identificacao, classificacao e priorizacao dos CRs de um produto em uma empresa automobilistica devido a classificacao dos SAs para atender esses CRs e, por fim, o ranking dos fornecedores. A primeira preocupacao no QFD tradicional e quantificar as relacoes entre CRs e ECs com base em conjuntos classicos. Obviamente, em situacoes praticas, muitas vezes e dificil para os especialistas fornecerem as suas opinioes usando valores exatos devido a complexidade ambiental e experiencia limitada. A segunda preocupacao refere-se a determinacao das importancias dos CRs com base nas avaliacoes dos clientes sem ter uma comparacao estruturada de pares entre os CRs. Alem disso, ignorar o comportamento de preferencia de quem toma a decisao usando um metodo de agregacao linear no QFD tradicional pode ser considerado como uma terceira preocupacao. Por outro lado, determinar os ECs cruciais no QFD e frequentemente considerado como MCDM. De forma a resolver este problema, nesta tese, considerando a incerteza dos dados, pretende-se integrar o modelo Kano, QFD e procedimentos MCDM numa metodologia hibrida.
546 $a English
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650 4 $a Sustainability. $3 1029978
650 4 $a European studies. $3 3168420
690 $a 0640
690 $a 0440
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690 $a 0338
710 2 $a Universidade do Minho (Portugal). $e degree granting institution. $3 3765699
720 1 $a Domingues, Jose Pedro Teixeira $e degree supervisor.
720 1 $a Sampaio, Paulo $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-03A.
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791 $a Ph.D.
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