Focusing on the importance of the application of statistical techniques, this book covers the design of experiments and stochastic modeling in textile engineering. Textile Engineering: Statistical Techniques, Design of Experiments and Stochastic Modeling focuses on the analysis and interpretation of textile data for improving the quality of textile processes and products using various statistical techniques.
FEATURES
Explores probability, random variables, probability distribution, estimation, significance test, ANOVA, acceptance sampling, control chart, regression and correlation, design of experiments and stochastic modeling pertaining to textiles
Presents step-by-step mathematical derivations
Includes MATLAB (R) codes for solving various numerical problems
Consists of case studies, practical examples and homework problems in each chapter
This book is aimed at graduate students, researchers and professionals in textile engineering, textile clothing, textile management and industrial engineering. This book is equally useful for learners and practitioners in other scientific and technological domains.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Academic, Postgraduate, and Professional
Illustrationen
178 s/w Abbildungen, 3 s/w Photographien bzw. Rasterbilder, 175 s/w Zeichnungen, 168 s/w Tabellen
168 Tables, black and white; 175 Line drawings, black and white; 3 Halftones, black and white; 178 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
Dicke: 26 mm
Gewicht
ISBN-13
978-0-367-53276-5 (9780367532765)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Autor*in
Government College of Engineering and Textile Technology, India
Government College of Engineering and Textile Technology, Berhampore, West Bengal, India
National Institute of Fashion Technology, Hyderabad, India
1. Introduction 2. Representation and Summarization of Data 3. Probability 4. Discrete Probability Distribution 5. Continuous Probability Distributions 6. Sampling Distribution and Estimation 7. Test of Significance 8. Analysis of Variance 9. Regression and Correlation 10. Design of Experiments 11. Statistical Quality Control 12. Stochastic Modelling