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Industrial design of experiments : a case study approach for design and process optimization / Sammy Shina.

Shina, Sammy G., author.
2022
TA160 .S55 2022
Available Online
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Title
Industrial design of experiments : a case study approach for design and process optimization / Sammy Shina.
Author
Shina, Sammy G., author.
ISBN
9783030862671 (electronic bk.)
3030862674 (electronic bk.)
9783030862664
3030862666
DOI
https://doi.org/10.1007/978-3-030-86267-1
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource : illustrations (some color)
Item Number
10.1007/978-3-030-86267-1 doi
Call Number
TA160 .S55 2022
Dewey Decimal Classification
620.0072/4
Summary
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. 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; Includes industrial case studies, worked examples and detailed solutions to problems.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 26, 2022).
Available in Other Form
Print version: 9783030862664
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Presentations, Statistical Distributions, Quality Tools and Relationship to DoE
Samples and Populations: Statistical Tests for Significance of Mean and Variability
Regression, Treatments, DoE Design and Modelling Tools
Two-Level Factorial Design and Analysis Techniques
Three-Level Factorial Design and Analysis Techniques
DoE Error Handling, Significance and Goal Setting
DoE Reduction Using Confounding and Professional Experience
Multiple Level Factorial Design and DoE Sequencing Techniques
Variability Reduction Techniques and Combining with Mean Analysis
Strategies for Multiple Outcome Analysis and Summary of DoE Case Studies and Techniques. .

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