MA4158 Statistical Applications in Textile Engineering Syllabus:
MA4158 Statistical Applications in Textile Engineering Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To understand the basics of random variables and point estimation with emphasis on the standard distributions.
To apply the small and large sample tests through Tests of hypothesis.
To understand the concept of analysis of variance and use it to investigate non- parametric model.
To monitor a process and detect a situation when the process is out of control.
To apply the concept of analysis of variance and use it to investigate factorial dependence.
UNIT I PROBABILITY DISTRIBUTION AND ESTIMATIONS
Applications of Binomial, Poisson, Normal, t, Exponential, Chi-square, F and Weibull distributions in textile engineering – Point estimates and interval estimations of the parameters of the distribution functions.
UNIT II HYPOTHESIS TESTING
Sampling distribution – Significance tests applicable to textile parameters – Normal test, t – test, Chi – square test and F – test – p-values – Selection of sample size and significance levels with relevance to textile applications – Acceptance sampling.
UNIT III ANALYSIS OF VARIANCE AND NON-PARAMETRIC TESTS
Analysis of variance for different models – Non – parametric tests – Sign test – Rank test – Concordance test.
UNIT IV PROCESS CONTROL AND CAPABILITY ANALYSIS
Control charts for variables and attributes – Basis, Development, Interpretation, Sensitizing rules, Average run length – Process capability analysis.
UNIT V DESIGN AND ANALYSIS OF EXPERIMENTS
2k full-factorial designs – Composite designs – Robust designs – Development of regression Models – Regression coefficients – Adequacy test – Process optimizations.
TOTAL: 60 PERIODS
COURSE OUTCOMES:
At the end of the course, students will be able to
Analyze the performance in terms of probabilities, distributions and point estimation achieved by the determined solutions.
Apply the basic principles underlying statistical inference (estimation and hypothesis testing).
Demonstrate the knowledge of applicable large sample theory of estimators and tests.
Identify the applicable sample theory of estimators and tests.
Obtain a better understanding of the importance of the methods in modern industrial processes.
REFERENCES:
1. Douglas C. Montgomery, “Design and analysis of experiments”, 8th Edition, John Wiley & Sons, Singapore, 2013.
2. Leaf G.A.V., “Practical Statistics for the Textile Industry, Part I and II”, the Textile Institute, Manchester, 1984.
3. Montgomery D.C., “Introduction to Statistical Quality Control”, 6th Edition, John Wiley and Sons, Singapore, 2009.
4. Ronald D. Moen, Thomas W. Nolan, Lloyd P. Provost, “Quality improvement through planned experimentation’, 3rd Edition, McGraw-Hill, 2012.