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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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发表于 2025-3-21 19:50:59 | 显示全部楼层 |阅读模式
书目名称Industrial Design of Experiments
副标题A Case Study Approac
编辑Sammy Shina
视频video
概述Presents classical versus Taguchi DoE methodologies as well as techniques developed by the author for successful DoE.Offers a step-wise approach to DoE optimization and interpretation of results.Inclu
图书封面Titlebook: Industrial Design of Experiments; A Case Study Approac Sammy Shina Textbook 2022 The Editor(s) (if applicable) and The Author(s), under exc
描述This textbook provides the tools, techniques, and industry examples needed for the successful implementation of design of experiments (DoE) in engineering and manufacturing applications. It contains a high-level engineering analysis of key issues in the design, development, and successful analysis of industrial DoE, focusing on the design aspect of the experiment and then on interpreting the results. Statistical analysis is shown without formula derivation, and readers are directed as to the meaning of each term in the statistical analysis.. .Industrial Design of .Experiments: A Case Study Approach for Design and Process Optimization .is designed for graduate-level DoE, engineering design, and general statistical courses, as well as professional education and certification classes. Practicing engineers and managers working in multidisciplinary product development will find it to be an invaluable reference that provides all the information needed to accomplish a successful DoE. .
出版日期Textbook 2022
关键词Analysis of Experiments; DoE; Quality; Optimization; Taguchi Method; Saturated design; Factorial design; Mu
版次1
doihttps://doi.org/10.1007/978-3-030-86267-1
isbn_softcover978-3-030-86269-5
isbn_ebook978-3-030-86267-1
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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发表于 2025-3-21 22:34:52 | 显示全部楼层
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
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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.
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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.
发表于 2025-3-23 00:56:05 | 显示全部楼层
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
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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.
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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
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