CIE347 Design of Experiments Syllabus:
CIE347 Design of Experiments Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES:
• Impart knowledge on principles and steps in designing a statistically designed experiment.
• Build foundation in analysing the data in single factor experiments and to perform post hoc tests.
• Provide knowledge on analysing the data in factorial experiments.
• Educate on analysing the data analysis in special experimental designs and Response Surface Methods.
• Impart knowledge in designing and analysing the data in Taguchi’s Design of Experiments to improve Process/Product quality.
UNIT I FUNDAMENTALS OF EXPERIMENTAL DESIGNS
Hypothesis testing – single mean, two means, dependant/ correlated samples – confidence intervals, Experimentation – need, Conventional test strategies, F-test, terminology, basic principles of design, steps in experimentation – choice of sample size – Normal and half normal probability plot – simple linear and multiple linear regression, Analysis of variance.
UNIT II SINGLE FACTOR EXPERIMENTS
Completely Randomized Design- effect of coding the observations- model adequacy checking – estimation of model parameters, residuals analysis- treatment comparison methods Duncan’s multiple range test, Newman-Keuel’s test, Fisher’s LSD test, Tukey’s test- Testing using contrasts Randomized Block Design – Latin Square Design- Graeco Latin Square Design – Applications.
UNIT III FACTORIAL DESIGNS
Main and Interaction effects – Two and three factor full factorial designs- Fixed effects and random effects model – Rule for sum of squares and Expected Mean Squares- 2 K Design with two and three factors- Yate’s Algorithm- fitting regression model- Randomized Block Factorial Design.
UNIT IV SPECIAL FACTORIAL DESIGNS
Blocking and Confounding in 2K Designs- blocking in replicated design- 2 K Factorial Design in two blocks- Complete and partial confounding- Confounding 2K Design in four blocks – Twolevel Fractional Factorial Designs- Construction of one-half and one-quarter fraction of 2K Design- Introduction to Response Surface Methods
UNIT V TAGUCHI METHODS
Design of experiments using Orthogonal Arrays, Data analysis from Orthogonal Experiments Response Graph Method, ANOVA- Attribute data analysis- Robust design- noise factors, Signal to Noise ratios, Inner/outer OA design- case studies.
COURSE OUTCOMES:
CO1: Understand the fundamental principles of Design of Experiments.
CO2: Analyze data in the single factor experiments.
CO3: Analyze data in the multifactor experiments.
CO4: Understand the special experimental designs & Response Surface Methods.
CO5: Apply Taguchi based approach to evaluate quality.
TEXT BOOKS
1. Krishnaiah, K. and Shahabudeen, P. Applied Design of Experiments and Taguchi Methods, PHI learning private Ltd., 2012.
2. Montgomery, D.C., Design and Analysis of Experiment, Minitab Manual, John Wiley and Sons, Seventh edition, 2010