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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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