Design of Experiments detail syllabus for Industrial Engineering & Management (Ind Engg & Mang), 2017 regulation is taken from Anna University official website and presented for students of Anna University. The details of the course are: course code (IE8791), Category (PC), Contact Periods/week (3), Teaching hours/week (3), Practical Hours/week (0). The total course credits are given in combined syllabus.
For all other ind engg & mang 6th sem syllabus for be 2017 regulation anna univ you can visit Ind Engg & Mang 6th Sem syllabus for BE 2017 regulation Anna Univ Subjects. The detail syllabus for design of experiments is as follows.”
Aims:
This course aims to introduce students how to statistically plan, design and execute industrial experiments for process understanding and improvement in both manufacturing and service environments
Course Objective:
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Unit I
Fundamentals of Experimental Designs
Hypothesis testing – single mean, two means, dependant/ correlated samples – confidence intervals, Experimentation – need, Conventional test strategies, Analysis of variance, 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, testing using 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- Duncans multiple range test, Newman-Keuels test, Fishers LSD test, Tukeys test- testing using contrasts-Randomized Block Design – Latin Square Design- Graeco Latin Square Design – Applications.
Unit III
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Unit IV
Special Experimental Designs
Blocking and Confounding in 2K Designs- blocking in replicated design- 2K Factorial Design in two blocks- Complete and partial confounding- Confounding 2K Design in four blocks- Two level Fractional Factorial Designs- one-half fraction of 2K Design, design resolution, Construction of one-half fraction with highest design resolution, one-quarter fraction of 2K Design- introduction to response surface methods, central composite design.
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 Outcome:
- To understand the fundamental principles of Classical Design of Experiments
- To apply DOE for process understanding and optimisation
- To describe the Taguchis approach to experimental design for process performance robustness
- To apply Taguchi based approach to evaluate quality
Text Books:
- Douglas C. Montgomery, Design and Analysis of Experiments, John Wiley and sons, 2012.
References:
- Box, G. E., Hunter,W.G., Hunter, J.S., Hunter,W.G., Statistics for Experimenters: Design, Innovation, and Discovery, 2nd Edition, Wiley, 2005.
- Krishnaiah K, and Shahabudeen P, Applied Design of Experiments and Taguchi Methods, PHI, India, 2011.
- Phillip J. Ross, Taguchi Techniques for Quality Engineering, Tata McGraw-Hill, India, 2005.
For detail syllabus of all other subjects of BE Ind Engg & Mang, 2017 regulation do visit Ind Engg & Mang 6th Sem syllabus for 2017 Regulation.
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