Industrial Design of Experiments

A Case Study Approach for Design and Process Optimization
1. Auflage 2022
ISBN: 978-3-030-86266-4
Verlag: Springer International Publishing

Buch, Englisch, 368 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 836 g

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.

Zielgruppe

Graduate

Autoren/Hrsg.

Shina, Sammy

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Technische Wissenschaften Technik Allgemein Konstruktionslehre und -technik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik
• Geisteswissenschaften Design Produktdesign, Industriedesign
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau Konstruktionslehre, Bauelemente, CAD
• Wirtschaftswissenschaften Betriebswirtschaft Betriebswirtschaft: Theorie & Allgemeines

Inhaltsverzeichnis

1) Presentations, Statistical Distributions, Quality Tools and Relationship to DoE2) Samples and Populations: Statistical Tests for Significance of Mean and Variability3) Regression, Treatments, DoE Design and Modelling Tools. 4) Two-Level Factorial Design and Analysis Techniques5) Three-Level Factorial Design and Analysis Techniques 6) DoE Error Handling, Significance and Goal Setting 7) DoE Reduction Using Confounding and Professional Experience 8) Multiple Level Factorial Design and DoE Sequencing Techniques9) Variability Reduction Techniques and Combining with Mean Analysis 10) Strategies for Multiple Outcome Analysis and Summary of DoE Case Studies and Techniques 

Über Autor(innen)

Sammy G. Shina, Ph.D., P.E., is a Professor of Mechanical Engineering (ME) at the University of Massachusetts Lowell. His research interests and teaching include six sigma, design of experiments, statistical quality control, product design and manufacturing, engineering project management, and green electronics. He is the founder of the New England Lead Free Electronics Consortium, which researches, tests, and evaluates materials and processes for lead- free RoHS compliance and conversion to nanotechnology. The consortium received the EPA regional Merit award. Dr. Shina has worked and consulted for a number of technology companies developing new products and state-of-the-art manufacturing technologies.He received BS degrees in Electrical Engineering and Industrial Management from the Massachusetts Institute of Technology, an MS in Computer Science from Worcester Polytechnic Institute, and a PhD in Mechanical Engineering from Tufts University. He is the author of several books and more than 120 papers on concurrent engineering, six sigma, green design, and engineering project management.