06ME847-Design Of Experiments |
PART – A |
UNIT I: |
INTRODUCTION: Strategy of Experimentation, Typical applications of
Experimental design, Basic Principles, Guidelines for Designing
Experiments.
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UNIT II: |
BASIC STATISTICAL CONCEPTS: Concepts of random variable,
probability, density function cumulative distribution function. Sample and
population, Measure of Central tendency; Mean median and mode, Measures
of Variability, Concept of confidence level. Statistical Distributions: Normal,
Log Normal & Weibull distributions. Hypothesis testing, Probability plots,
choice of sample size. Illustration through Numerical examples.
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UNIT III: |
EXPERIMENTAL DESIGN: Classical Experiments: Factorial
Experiments: Terminology: factors, levels, interactions, treatment
combination, randomization, Two-level experimental designs for two factors
and three factors. Three-level experimental designs for two factors and three
factors, Factor effects, Factor interactions, Fractional factorial design,
Saturated Designs, Central composite designs. Illustration through Numerical
examples.
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UNIT IV: |
ANALYSIS AND INTERPRETATION METHODS: Measures of
variability, Ranking method, Column effect method & Plotting method,
Analysis of variance (ANOVA) in Factorial Experiments: YATE’s algorithm
for ANOVA, Regression analysis, Mathematical models from experimental
data. Illustration through Numerical examples.
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PART – B |
UNIT V: |
QUALITY BY EXPERIMENTAL DESIGN: Quality, Western and
Taguchi’s quality philosophy, elements of cost, Noise factors causes of
variation. Quadratic loss function & variations of quadratic loss function.
Robust Design: Steps in Robust Design: Parameter design and Tolerance
Design. Reliability Improvement through experiments, Illustration through
Numerical examples.
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UNIT VI: |
EXPERIMENT DESIGN USING TAGUCHI’S ORTHOGONALARRAYS: Types of Orthogonal Arrays, selection of standard orthogonal
arrays, Linear graphs and Interaction assignment, Dummy level Technique,
Compound factor method, Modification of linear graphs. Illustration through
Numerical examples.
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UNIT VII: |
SIGNAL TO NOISE RATIO: Evaluation of sensitivity to noise. Signal to
Noise ratios for static problems: Smaller-the-better type, Nominal-the –
better-type, Larger-the-better type. Signal to Noise ratios for Dynamic
problems. Illustration through Numerical examples.
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UNIT VIII: |
PARAMETER AND TOLERANCE DESIGN: Parameter and tolerance
design concepts, Taguchi’s inner and outer arrays, parameter design strategy,
tolerance design strategy. Illustration through Numerical examples.
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REFERENCE |
TEXT BOOKS: |
1. Design and Analysis of Experiments, Douglas C. Montgomery, 5th
Edition Wiley India Pvt. Ltd. 2007
2. Quality Engineering using Robust Design, Madhav S. Phadke,
Prentice Hall PTR, Englewood Cliffs, New Jersy 07632, 1989.
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Reference Books |
1. Quality by Experimental Design, Thomas B. Barker, Marcel
Dekker, Inc ASQC Quality Press.1985.
2. Experiments Planning, analysis, and parameter Designoptimization, C.F. Jeff Wu Michael Hamada, John Wiley Editions.
2002.
3. Reliability Improvement by Experiments, W.L. Condra, Marcel
Dekker, Inc ASQC Quality Press.1985.
4. Taguchi Techniques for Quality Engineering, Phillip J. Ross, 2nd
Edn. McGraw Hill International Editions, 1996.
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