Syllabus
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Course Code: ELECTIVE-V MTIP-203 Course Name: Design of Experiments |
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| MODULE NO / UNIT | COURSE SYLLABUS CONTENTS OF MODULE | NOTES |
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| 1 | Introduction to Designed Experiments: Introduction: Strategy of experimentation, Some typical applications of
experimental design, Basic principles, Guidelines for designing experiments, Using statistical design in experimentation,
A Checklist for Planning experiments, Introduction to Minitab, Interface of Minitab, Customizing Minitab, Entering Data,
Graphing Data, Printing Data and Graphs, Saving and Retrieving information. Basic Statistical Methods: Introduction, Basic statistical concepts, Types of Data, Graphical Presentation of Data. Descriptive Statistics: Measure of Location, Measure of Variation, The Normal Distribution, Counting, Minitab Commands to Calculate Descriptive Statistics. Inferential Statistics: The Distribution of Sample Means (R Known), Confidence Interval for the Population Mean (σ Known), Hypothesis testing for one sample mean (σ Known), Hypothesis test for two sample means, Testing for Normality, Hypothesis test and Confidence Intervals with Minitab. |
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| 2 | Analysis of Variance: Introduction to Analysis of Variance, ANOVA assumptions and Validation, ANOVA Table, The
sum of square approach to ANOVA calculations, Analysis of the fixed Effect model, Decomposition of the Total sum of
squares. Statistical analysis, Estimation of the Model Parameters, Unbalanced Data, Model Accuracy Check, Practical
interpretation of results. ANOVA with Minitab Factorial Experiments: Basic definition and principles, Advantages of factorials, Two level factorial design, The 21 Factorial Experiment, The 22 Factorial Experiment, The 23 Factorial Design, Addition of Centre Cells to 2k Designs. General Procedure for Analysis of 2k designs. 2k Factorial Designs in Minitab. |
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| 3 | Introduction to Taguchi Method: Introduction, Taguchi Quality loss function, Orthogonal Array, Properties of Orthogonal Array, Minimum number of experiments to be conducted, Static Problems, Dynamic Problems, Assumptions of the Taguchi method, Steps in Taguchi Method, Assessment of Factors and Interactions, Selection and Application of Orthogonal arrays, Data Analysis from Taguchi Experiments, Variable Data with main factors only, Variable Data with Interactions, Attribute Data Analysis, Confirmation Experiment, Confidence Intervals, Robust Design Approach. Applications of Taguchi Method using Minitab. | |
| 4 | Introduction to Response Surface Methodology: Introduction, Terms in Quadratic Models, The method of steepest ascent, Analysis of Second order response surfaces, Experimental design for fitting response surfaces, 2k Designs with Centers, 3k Factorial Designs, Box-Behnken Designs, Central Composite Designs, Analysis of Data from RSM Designs, Design Considerations for Response Surface Experiments. Response Surface Designs in Minitab. | |
