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Record W2062742889 · doi:10.1155/2014/627093

Innovative Product Design Based on Comprehensive Customer Requirements of Different Cognitive Levels

2014· article· en· W2062742889 on OpenAlexaff
Xiaolong Li, Wu Zhao, Yake Zheng, Rui Wang, Wang Chen

Bibliographic record

VenueThe Scientific World JOURNAL · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality Function Deployment in Product Design
Canadian institutionsWilfrid Laurier UniversityUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsQuality function deploymentTRIZComputer scienceProduct (mathematics)Systems engineeringHouse of QualityVoice of the customerProduct designProcess (computing)Customer satisfactionProcess managementQuality (philosophy)Analytic hierarchy processFunction (biology)New product developmentManufacturing engineeringEngineeringBusinessOperations researchService qualityCustomer retentionMarketingMathematics

Abstract

fetched live from OpenAlex

To improve customer satisfaction in innovative product design, a topology structure of customer requirements is established and an innovative product approach is proposed. The topology structure provides designers with reasonable guidance to capture the customer requirements comprehensively. With the aid of analytic hierarchy process (AHP), the importance of the customer requirements is evaluated. Quality function deployment (QFD) is used to translate customer requirements into product and process design demands and pick out the technical requirements which need urgent improvement. In this way, the product is developed in a more targeted way to satisfy the customers. the theory of innovative problems solving (TRIZ) is used to help designers to produce innovative solutions. Finally, a case study of automobile steering system is used to illustrate the application of the proposed approach.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.121
GPT teacher head0.297
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2014
Admission routes1
Has abstractyes

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