CX4003 Design and Analysis of Experiments Syllabus:
CX4003 Design and Analysis of Experiments Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
• To learn about the statistical tools and design principles of experiments
• To learn about the usage of single factor testing methods
• To learn and apply the Factorial design techniques
• To know various special experimental design techniques
• To learn about various Taguchi’s Techniques
UNIT I CONCEPTS AND TERMINOLOGY
Review of hypothesis testing – P Value, ―t‖Vs paired―t‖ test, simple comparative experiment, planning of experiment – steps, Terminology – factors, levels, variables, Design principles – replication, randomization, blocking, confounding, Analysis of variance, sum of squares, degrees of freedom.
UNIT II SINGLE FACTOR EXPERIMENTS
Completely randomized design, Randomized block design, effect of coding the observations, Latin Square design, orthogonal contrasts, comparison of treatment means – Duncan‘s multiple range test, Newman-Keuel’s test, Fisher‘s LSD test, Tukey’s test.
UNIT III FACTORIAL EXPERIMENTS
Main and interaction effects, Rules for sum of squares and expected mean square, two and three factor full factorial design, 2k designs with two and three factors, Yate’s algorithm, practical applications
UNIT IV SPECIAL EXPERIMENTAL DESIGNS
Blocking and confounding in 2k design, nested design, split – plot design, two level fractional factorial design, fitting regression models, introduction to response surface methods- Central composite design.
UNIT V TAGUCHI TECHNIQUES
Introduction, Orthogonal designs, data analysis using ANOVA and response graph, parameter design – noise factors, objective functions (S/N ratios), multi-level factor OA designs, applications
TOTAL : 45 PERIODS
COURSE OUTCOMES:
The students will be able to
CO1: Understand sampling and sampling distribution
CO2: Apply Hypothesis testing with different confidence intervals
CO3: Perform ANOVA and regression analysis
CO4: Perform statistically designed experiments with and without blocking
CO5: Model the given data using Response Surface Methodology
REFERENCES
1. Angela M. Dean and Daniel Voss, Design and Analysis of Experiments, Springer texts in Statistics, 2000
2. Douglus C. Montgomery, Design and Analysis of Experiments, John Wiley & Sons, 2005
3. Philip J. Ross, Taguchi Techniques for Quality Engineering, Prentice Hall, 1989
4. George W Cobb., – Introduction to Design and Analysis of Experiments, Wiley India Exclusive (CBS), 2015
5. Panneerselvam R., – Design and Analysis of Experiments, PHI Learning, 2012