Description
Textile Engineering
Statistical Techniques, Design of Experiments and Stochastic Modeling
Authors: Ghosh Anindya, Saha Bapi, Mal Prithwiraj
Language: EnglishSubjects for Textile Engineering:
Keywords
Drape Coefficient; Lower Boundary Point; Probability; Random Dynamical Systems; Sampling; Cotton Fibre Lengths; Analysis of Variance; ATI; Regression; AOQ; Experiments; Stochastic Differential Equation; Modeling; Probability Density Curve; Binomial Distribution; OC Curve; Data Set; Multiple Linear Regression; MGF; Average Absolute Distance; Discrete Random Variable; Control Chart; AOQ Curve; Density Histogram; Untreated Fabric Samples; Proportion Defective; Euler Maruyama Approximation; Yarn Tenacity; Acceptance Sampling Scheme; UL; Yarn Strength
214.69 €
In Print (Delivery period: 14 days).
Add to cart the book of Ghosh Anindya, Saha Bapi, Mal Prithwiraj· 15.6x23.4 cm · Hardback
Description
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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® 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.
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