{"id":59791,"date":"2023-09-06T08:08:51","date_gmt":"2023-09-06T08:08:51","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/el3010-design-of-experiments-syllabus-for-cee-2021-regulation-professional-elective-ii\/"},"modified":"2023-09-06T08:08:51","modified_gmt":"2023-09-06T08:08:51","slug":"el3010-design-of-experiments-syllabus-for-cee-2021-regulation-professional-elective-ii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/el3010-design-of-experiments-syllabus-for-cee-2021-regulation-professional-elective-ii\/","title":{"rendered":"EL3010: Design of Experiments syllabus for CEE 2021 regulation (Professional Elective-II)"},"content":{"rendered":"

Design of Experiments detailed syllabus for Chemical & Electrochemical Engineering (CEE) for 2021 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the CEE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Chemical & Electrochemical Engineering 5th Sem scheme and its subjects, do visit CEE 5th Sem 2021 regulation scheme<\/a>. For Professional Elective-II scheme and its subjects refer to CEE Professional Elective-II syllabus scheme<\/a>. The detailed syllabus of design of experiments is as follows. <\/p>\n

Course Objectives:<\/h4>\n

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Unit I<\/h4>\n

FUNDAMENTALS OF EXPERIMENTAL DESIGNS\t9<\/strong>
\nHypothesis 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.\n<\/p>\n

Unit II<\/h4>\n

SINGLE FACTOR EXPERIMENTS\t9<\/strong>
\nCompletely Randomized Design- effect of coding the observations- model adequacy checkingestimation of model parameters, residuals analysis- treatment comparison methods-Duncan\u2019s multiple range test, Newman-Keuel\u2019s test, Fisher\u2019s LSD test, Tukey\u2019s testtesting using contrasts-Randomized Block Design – Latin Square Design- Graeco Latin Square Design -Applications.\n<\/p>\n

Unit III<\/h4>\n

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Unit IV<\/h4>\n

SPECIAL EXPERIMENTAL DESIGN\t9<\/strong>
\nBlocking 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- 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\n<\/p>\n

Unit V<\/h4>\n

TAGUCHI METHODS\t9<\/strong>
\nDesign 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.\n<\/p>\n

Course Outcomes:<\/h4>\n