An integrated quality-function-deployment and stochastic-dominance-based decision-making approach for prioritizing product concept alternatives

Zeng-Qiang Wang; Zhen-Song Chen; Harish Garg; Yun Pu; Kwai-Sang Chin

doi:10.1007/s40747-022-00681-1

An integrated quality-function-deployment and stochastic-dominance-based decision-making approach for prioritizing product concept alternatives

Zeng-Qiang Wang
, Zhen-Song Chen^*
, Harish Garg
, Yun Pu
, Kwai-Sang Chin

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

10 Citations (Scopus)

52 Downloads (CityUHK Scholars)

Abstract

For continuous growth and sustaining the competitiveness of a company, product developers spend most of their time making crucial decisions to address a great variety of unpredictable and uncontrollable information. Several mathematical approaches have already been adopted to aid the developers in selecting the best product concept for meeting customers' requirements and exceeding their expectations. However, those methods do not cope with fully revealed developers' preferences and do not take into account the random distribution of the target values of engineering characteristics (ECs). In this paper, the application of a quality function deployment (QFD)-based model and a stochastic dominance-based method is presented for product concept development. The first phase in the approach is to construct a product planning house of quality (PPHoQ), which is the core and the engine of the entire QFD model. This model depicts the relationship between the customers' requirements (CRs) and the ECs for a product. The proposed approach addresses both the relationships between CRs and ECs, in addition to the correlations among the ECs. In this study, developers are invited to express their preferences using different types of linguistic terms dependent on their diverse backgrounds and understanding levels of the product. Based on the outcomes of the PPHoQ process, a variety of alternative concepts can be created. The alternatives are then prioritized and ranked in the second phase. The proposed approach facilitates the random distribution with stochastic variables rather than fuzzy methods to obtain more realistic product concept alternatives. Several examples and comparative results further illustrate that unbalanced linguistic terms and stochastic dominance efficiently endow the product concept selection model with uncertain information and the random distribution in a realistic style.

Original language	English
Pages (from-to)	2541–2556
Journal	Complex & Intelligent Systems
Volume	8
Issue number	3
Online published	14 Feb 2022
DOIs	https://doi.org/10.1007/s40747-022-00681-1
Publication status	Published - Jun 2022

Funding

This work was supported by the National Natural Science Foundation of China (Grant nos. 72171182, 71801175, 71871171, 71971182, and 72031009), the Theme-based Research Projects of the Research Grants Council (Grant no. T32-101/15-R), the Ger/HKJRS project (Grant no. G-CityU103/17), and the City University of Hong Kong SRG (Grant no. 7004969).

Research Keywords

Quality function deployment
Product planning house of quality
Product concept alternative
Stochastic dominance
Unbalanced linguistic term
ELECTRE-III
FUZZY-QFD
ENGINEERING CHARACTERISTICS
DESIGN
SELECTION
SUPPORT
REQUIREMENTS
OPTIMIZATION
MANAGEMENT
REGRESSION

Publisher's Copyright Statement

This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

RGC-funded

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10.1007/s40747-022-00681-1

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Cite this

@article{84564a291cc849d89ee36040e6a19889,

title = "An integrated quality-function-deployment and stochastic-dominance-based decision-making approach for prioritizing product concept alternatives",

abstract = "For continuous growth and sustaining the competitiveness of a company, product developers spend most of their time making crucial decisions to address a great variety of unpredictable and uncontrollable information. Several mathematical approaches have already been adopted to aid the developers in selecting the best product concept for meeting customers' requirements and exceeding their expectations. However, those methods do not cope with fully revealed developers' preferences and do not take into account the random distribution of the target values of engineering characteristics (ECs). In this paper, the application of a quality function deployment (QFD)-based model and a stochastic dominance-based method is presented for product concept development. The first phase in the approach is to construct a product planning house of quality (PPHoQ), which is the core and the engine of the entire QFD model. This model depicts the relationship between the customers' requirements (CRs) and the ECs for a product. The proposed approach addresses both the relationships between CRs and ECs, in addition to the correlations among the ECs. In this study, developers are invited to express their preferences using different types of linguistic terms dependent on their diverse backgrounds and understanding levels of the product. Based on the outcomes of the PPHoQ process, a variety of alternative concepts can be created. The alternatives are then prioritized and ranked in the second phase. The proposed approach facilitates the random distribution with stochastic variables rather than fuzzy methods to obtain more realistic product concept alternatives. Several examples and comparative results further illustrate that unbalanced linguistic terms and stochastic dominance efficiently endow the product concept selection model with uncertain information and the random distribution in a realistic style.",

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author = "Zeng-Qiang Wang and Zhen-Song Chen and Harish Garg and Yun Pu and Kwai-Sang Chin",

year = "2022",

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language = "English",

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An integrated quality-function-deployment and stochastic-dominance-based decision-making approach for prioritizing product concept alternatives. / Wang, Zeng-Qiang; Chen, Zhen-Song; Garg, Harish et al.
In: Complex & Intelligent Systems, Vol. 8, No. 3, 06.2022, p. 2541–2556.

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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T1 - An integrated quality-function-deployment and stochastic-dominance-based decision-making approach for prioritizing product concept alternatives

AU - Wang, Zeng-Qiang

AU - Chen, Zhen-Song

AU - Garg, Harish

AU - Pu, Yun

AU - Chin, Kwai-Sang

PY - 2022/6

Y1 - 2022/6

N2 - For continuous growth and sustaining the competitiveness of a company, product developers spend most of their time making crucial decisions to address a great variety of unpredictable and uncontrollable information. Several mathematical approaches have already been adopted to aid the developers in selecting the best product concept for meeting customers' requirements and exceeding their expectations. However, those methods do not cope with fully revealed developers' preferences and do not take into account the random distribution of the target values of engineering characteristics (ECs). In this paper, the application of a quality function deployment (QFD)-based model and a stochastic dominance-based method is presented for product concept development. The first phase in the approach is to construct a product planning house of quality (PPHoQ), which is the core and the engine of the entire QFD model. This model depicts the relationship between the customers' requirements (CRs) and the ECs for a product. The proposed approach addresses both the relationships between CRs and ECs, in addition to the correlations among the ECs. In this study, developers are invited to express their preferences using different types of linguistic terms dependent on their diverse backgrounds and understanding levels of the product. Based on the outcomes of the PPHoQ process, a variety of alternative concepts can be created. The alternatives are then prioritized and ranked in the second phase. The proposed approach facilitates the random distribution with stochastic variables rather than fuzzy methods to obtain more realistic product concept alternatives. Several examples and comparative results further illustrate that unbalanced linguistic terms and stochastic dominance efficiently endow the product concept selection model with uncertain information and the random distribution in a realistic style.

AB - For continuous growth and sustaining the competitiveness of a company, product developers spend most of their time making crucial decisions to address a great variety of unpredictable and uncontrollable information. Several mathematical approaches have already been adopted to aid the developers in selecting the best product concept for meeting customers' requirements and exceeding their expectations. However, those methods do not cope with fully revealed developers' preferences and do not take into account the random distribution of the target values of engineering characteristics (ECs). In this paper, the application of a quality function deployment (QFD)-based model and a stochastic dominance-based method is presented for product concept development. The first phase in the approach is to construct a product planning house of quality (PPHoQ), which is the core and the engine of the entire QFD model. This model depicts the relationship between the customers' requirements (CRs) and the ECs for a product. The proposed approach addresses both the relationships between CRs and ECs, in addition to the correlations among the ECs. In this study, developers are invited to express their preferences using different types of linguistic terms dependent on their diverse backgrounds and understanding levels of the product. Based on the outcomes of the PPHoQ process, a variety of alternative concepts can be created. The alternatives are then prioritized and ranked in the second phase. The proposed approach facilitates the random distribution with stochastic variables rather than fuzzy methods to obtain more realistic product concept alternatives. Several examples and comparative results further illustrate that unbalanced linguistic terms and stochastic dominance efficiently endow the product concept selection model with uncertain information and the random distribution in a realistic style.

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KW - Unbalanced linguistic term

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KW - ENGINEERING CHARACTERISTICS

KW - DESIGN

KW - SELECTION

KW - SUPPORT

KW - REQUIREMENTS

KW - OPTIMIZATION

KW - MANAGEMENT

KW - REGRESSION

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DO - 10.1007/s40747-022-00681-1

M3 - RGC 21 - Publication in refereed journal

SN - 2199-4536

VL - 8

SP - 2541

EP - 2556

JO - Complex & Intelligent Systems

JF - Complex & Intelligent Systems

IS - 3

ER -

An integrated quality-function-deployment and stochastic-dominance-based decision-making approach for prioritizing product concept alternatives

Abstract

Funding

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

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