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(DOE) is a structured methodology to optimize product and process designs, to accelerate the development cycle, to reduce development costs and to effectively trouble shoot manufacturing problems
DESIGN OF EXPERIMENTS (DOE)
89259 06892

Duration | 20 Hours (2hrs/day)
ELIGIBILITY:
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Pursuing (Final Year) / Completed Engineering graduates / Working professionals in Design, Mfg., Quality functions
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Basic knowledge on Statistics, Working knowledge in Excel
CERTIFICATION CRITERIA:
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Attendance – 90% Min
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Assignment completion – 100%
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Post test assessment score – 70% Min
HIGHLIGHTS
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DOE Explained with real time exercises and industry case studies
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Step by step approach to DOE – Design and analysis using Minitab
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End of Module Assessments enable instructor to ascertain whether students have understood the program
CONTENTS
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1. Introduction to DOE
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Experimental design
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Single factor experimentation
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Factorial notation
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Controllable & Response variables
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Planning for DOE
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Interactions
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2. DOE Design
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One Factor Experiments
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Full factorial & Fractional factorial designs
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Confounding
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Resolution
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Repeats and Replicates
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Randomization & Blocking
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3. DOE Analysis
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Practical, Graphical and Analytical approaches
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Main effects and Interaction effects
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Diagnostic plots
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ANOVA Model
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Multiple regression model
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Response optimization
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Using MiniTab for Analysis and optimization
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4. Taguchi Methods
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Robustness & Noise
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Parameter design
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Orthogonal Arrays
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Selection of Orthoganal arrays
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Signal to Noise Ratio (S/N)
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Analyzing Taguchi designs
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Optimization
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5. Response Surface Designs
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6. Multi response optimization – Grey Relational analysis
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Minitab Exercises for all DOE models
OUTCOMES
By The End Of Course The Learner Will Be Able To:
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Design and conduct experiments
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Analyse the DOE results using Minitab
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Optimize the product and process performance
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Take up research projects using DOE