Knowledge-based Decision Support System Quality Function Deployment (KBDSS-QFD) tool for assessment of building envelopes

Singhaputtangkul, Natee; Low, Sui Pheng; Teo, Ai Lin; Hwang, Bon‐Gang

doi:10.1016/j.autcon.2013.05.017

Cited by 40 publications

(25 citation statements)

References 33 publications

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“…The study has become the concept model of QFSbased benchmarking logic. Singhaputtangkul et al proposed a QFD assessment system for a building envelope [22]. Li et al suggested a QFD system combining a fuzzy-TOPSIS that is used in multicriteria decision-making [27].…”

Section: Literature Reviewmentioning

confidence: 99%

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QFD Based Benchmarking Logic Using TOPSIS and Suitability Index

Cho

Jin

Kim

et al. 2015

Mathematical Problems in Engineering

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Users' satisfaction on quality is a key that leads successful completion of the project in relation to decision-making issues in building design solutions. This study proposed QFD (quality function deployment) based benchmarking logic of market products for building envelope solutions. Benchmarking logic is composed of QFD-TOPSIS and QFD-SI. QFD-TOPSIS assessment model is able to evaluate users' preferences on building envelope solutions that are distributed in the market and may allow quick achievement of knowledge. TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) provides performance improvement criteria that help defining users' target performance criteria. SI (Suitability Index) allows analysis on suitability of the building envelope solution based on users' required performance criteria. In Stage 1 of the case study, QFD-TOPSIS was used to benchmark the performance criteria of market envelope products. In Stage 2, a QFD-SI assessment was performed after setting user performance targets. The results of this study contribute to confirming the feasibility of QFD based benchmarking in the field of Building Envelope Performance Assessment (BEPA).

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Section: Literature Reviewmentioning

confidence: 99%

“…The market's subjective assessment on novel technology and unfamiliar usability excludes new chance to improve the performance [22]. Moreover, performance criteria, as user satisfaction, have not been proposed.…”

Section: Introductionmentioning

confidence: 99%

QFD Based Benchmarking Logic Using TOPSIS and Suitability Index

Cho

Jin

Kim

et al. 2015

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…Singhaputtangkul et al proposed a QFD-based knowledge management system for building envelopes [19]. Li et al suggested another QFD-based knowledge management system combining itself with a fuzzy-TOPSIS that is used in a multicriteria decision-making method [20].…”

Section: Researches On the Evaluation Of Element Techniquementioning

confidence: 99%

Performance Requirements on Remodeling Apartment Housing and TOPSIS Evaluation

Cho

Jin

2015

Mathematical Problems in Engineering

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Functional improvement needed in remodeling projects is determined by users in a complex manner since remodeling projects require performance improvement against deterioration. This study defines fundamental Remodeling Performance Criteria (RPC) for apartment housing by referring to performance criteria of both domestic and international performance-related systems. In this case study, performance evaluation of Construction Element Method (CEM) for remodeling projects was conducted based on RPC. For the objective evaluation of CEM, performance scores were calculated and normalized by using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model, which is used in a multicriteria decision-making method. The TOPSIS evaluation model allows for a comprehensive and comparative analysis on the performance of the remodeling solution. The TOPSIS model in this study suggests a standard logic of performance evaluation for aged buildings as it analyzes the degree of deterioration at the prior remodeling phase and predicts the performance improvement level for CEM at the remodeling planning phase.

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“…Singgih et al (2013) applied QFD four phases to consider not only the quality but also factor in the time and cost in developing a products. Singhaputtangkul et al (2013) used QFD for decision-making problems when assessing building envelope materials and designs for a private high-rise residential building in the early design stage. Gilbert et al (2014) study proposed a new systematic approach to the conceptual design of construction projects -specifically temporary housing -by combining Quality Function Deployment (QFD) and Axiomatic Design (AD), which helped to ensure that the design meets customer's needs, as well as satisfies the design objectives in a logical sequence.…”

Section: Design Methodsmentioning

confidence: 99%

The Development of Conceptual Building Design Technology, Using Quality Function Deployment and Axiomatic Design

Lapinskienė

Martinaitis

2017

Science - Future of Lithuania

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abstract. Understanding issues early in the integrated design process is important, as this is when designers and engineers are able to have the largest impact on the final product. In this article the technology of conceptual architectural design for low energy buildings is proposed to address this issue. Here two methods -Quality function Deployment and Axiomatic design are used to develop the conception and to eliminate the main disadvantages of traditional building design. The integration of BIM, energy modelling (DesignBuilder) help to highlight the issue of energy efficiency at the early stage of building design, resulting in effective and more to posed requirements orientated design process.

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Knowledge-based Decision Support System Quality Function Deployment (KBDSS-QFD) tool for assessment of building envelopes

Cited by 40 publications

References 33 publications

QFD Based Benchmarking Logic Using TOPSIS and Suitability Index

QFD Based Benchmarking Logic Using TOPSIS and Suitability Index

Performance Requirements on Remodeling Apartment Housing and TOPSIS Evaluation

The Development of Conceptual Building Design Technology, Using Quality Function Deployment and Axiomatic Design

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