Course Archives Statistical Quality Control & Operations Research Unit
Course:Industrial Experimentation
Time: Currently offered
Syllabus
Past Exams

Syllabus: Introduction: What is experimentation? Why Experimentation? Role of experimental designs in industries. List of Design terminologies Experimental process from the point of view of a statistician, Concept of and components of Experimental Error. Identification and classification of factors. Historical overview: (a) Classical statistical design of experiments (R A Fisher to G.E.P BOX) (b) Quality Era: (Taguchi Method phase I, II, III) (c) Post Taguchi developments in Classical statistical design of experiments. (d) Current trends, eg. Computer experiments. Steps in a statistical design of experimental project. Basic principles.
Block Designs: Competently Randomized Design. Concept of blocking Paired comparisons as block design, Randomized complete block design, Latin square design, Residual analysis: assessment of Model, Problems. Use of Statistical software.
Classical Factorial Designs: 2^K and 3^K factorial designs, Statistical Analysis, Model adequacy checking, Fundamental principles regarding factorial effects (Sparsity, heredity, hierarchy principles). Analysis of a single replicates, use of normal and half normal plots. Confounding 2^K in two blocks, four blocks and in 2^P blocks, 3^K in 3, 9 and 3P blocks. 2k-p and 3k-p Fractional Factorial designs, ( Criteria for design selection: Concept of Design Resolution and Minimum Aberration Designs) Residual analysis: assessment of Model, Problems. Use of Statistical software.
Nested/Hierarchical Designs: Two stage nested design, Statistical analysis, estimation of model parameters, diagnostic checking. General m-stage nested designs. Design with nested and crossed factors.
Designs with randomization restriction: Split plot, split unit designs.
Response Surface Methodology: Introduction, Method of steepest ascent, Analysis of quadratic models, Response surface designs for first order and second order models, rotatable and orthogonal designs Equiradial, simplex, central composite, Box Behnken designs, Problems.
Mixture Designs Introduction, Simplex lattice designs (Scheffe). Simplex centroid designs, Extreme vertices designs, Response surface designs with mixtures-first order and second order model for constrained mixture spaces, Problems.
Taguchis Robust Designs (Phase II & III): Taguchis philosophy of quality engineering, Loss function, Taguchis Noise strategy contrasting Basic principles of classical experimentation. Three steps approach to robust design, Parameter designs, Inner array and outer array, Signal to noise ratios static and dynamic, Tolerance designs, Statistical analysis, Problems. Post Taguchi development in classical statistical design: Critique of Taguchi Methods.
Computer Experiments, Space Filling Designs (2): Introduction, etc

Reference Texts:
1. Design and Analysis of experiments: By D.C. Montgomery, J Wiley, NY
2. Statistics for Experimenter - An Introduction to data analysis and model building: By G.E.P. Box, W.G.Hunter, J Wiley, N.Y.
3. Design of Experiments - A-No-Name-Approach: By T.J Lorenzer and V.L. Anderson, Marcel Dekker, N. Y.
4. Experimental Designs: By W.G. Cochran and G.M. Cox, J Wiley, N.Y.
5. Design of Experiments _ A realistic approach: By V.L. Anderson and RA. Mcelean, Marcel Dekker, N.Y.
6. Statistical Design and Analysis of Experiments: By P.W.M. John, MacMillan.
7. The Design of Experiments: By RA Fisher, Hafner N.Y.
8. Statistical Design and Analysis of Industrial Experiments: By S.Ghosh, Marcel Dekker,N.Y.
9. Design and Analysis of Experiments: By M .N. Das and N.C. Giri, Wiley Eastern, N. Delhi
10. Empirical Model Building and Response Surface: By G.E.P. box and N.R Draper, J Wiley, N.Y.
11. Response Surface Methodology - Process and Product Optimisation Using Designed Experiments: By RH. Myers and D.C. Montgomery
12. Response Surface Designs and Analysis: By AI. Khuri and JA Cornel, Marcel Dekker, N.Y.
13. Introduction to Quality Engineering: By G. Taguchi, APO, UNIPUB, White Plains, N.Y.
14. Introduction to Off-line Quality Control: By G. Taguchi, Central Japan Quality Control Association, Nagoya, Japan.
15. System of Experimental Designs - Engineering Methods to Optimise Quality and Minimise Cost, UNIPUB/Kraus International: By White Plains, N.Y.
16. Experiments with Mixtures -Design, Model and the Analysis of Mixture Data: By J.A. Cornell. J. Wiley, N.Y.
17. Experiments, planning, Analysis and parameter Design Optimization: By C F Jeff Wu, Michael Hamada,John Wiley & Sons, Inc., New York,2000,ISBN:0-471-25511-4

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Past Exams
Midterm
 15.pdf 17.pdf
Semestral
 15.pdf 17.pdf
Supplementary and Back Paper
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[Indian Statistical Institute]