Titlebook: Industrial Design of Experiments; A Case Study Approac Sammy Shina Textbook 2022 The Editor(s) (if applicable) and The Author(s), under exc

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書目名稱Industrial Design of Experiments影響因子(影響力)




書目名稱Industrial Design of Experiments影響因子(影響力)學(xué)科排名




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書目名稱Industrial Design of Experiments讀者反饋




書目名稱Industrial Design of Experiments讀者反饋學(xué)科排名

煞費苦心

Data Presentations, Statistical Distributions, Quality Tools, and Relationship to DoE,ble sample sizes with examples and analysis. A hierarchical approach of using quality tools including TQM, DMAIC, Six Sigma, Control Charts and DoE to achieve world class quality is demonstrated. The proper sequence of using these tools is shown, depending on whether optimizing current or new proces

記憶

Samples and Populations: Statistical Tests for Significance of Mean and Variability,using F-Tests to indicate individual factor significance. In DoE terminology, they represent significance testing of two levels of a single factor, while DoE are statistical significance tests for multiple factors and levels.

Hearten

mechanical

引水渠

overture

DoE Error Handling, Significance, and Goal Setting,ources of error are discussed. A DoE case study will be shown with the mentioned error handling techniques to contrast their use and relative benefits. All error and significance calculations will be shown with visual techniques to highlight concepts used.

Kidnap

DoE Reduction Using Confounding and Professional Experience,nd L32. The use of interconnection diagrams to propose minimum confounding of main factors with two-way interactions are shown, as more factors are added to each OA with proper assignments of factors to columns. Case studies from previous chapters will be re-examined in the light of new concepts dev

過度

Multiple-Level Factorial Design and DoE Sequencing Techniques,scussed in this chapter explore techniques mentioned above for quickly solving design problems and new material or process selection. Decisions made by DoE teams are discussed and results analyzed using methodologies highlighted in this and previous chapters.

違法事實

Variability Reduction Techniques and Combining with Mean Analysis,esign or process mean or reducing variability. Design elements or process steps could be eliminated with reduced variability if validated by DoE mean and variability analysis. Greater efficiency using either scheme should be included in the overall DoE project recommendations. DoE case studies showi