DESIGN OF EXPERIMENTS (DOE)

2 Days Work Shop Presented By CTRI (CT Research Institute)

Research and Training wing of Western Thomson Group

COURSE OBJECTIVE

Design of experiments (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.

Today, Design of Experiments is viewed as a quality technology to achieve product excellence at lowest possible overall cost. It has been established in many different industries including electronics, aerospace, automotive, medical, food and pharmaceuticals, and chemical and process industries.

The effective use of sound statistical based experimental design methodology can lead to products that are easier to manufacture, have higher reliability and have enhanced field performance.

At the end of the course the participant will be able to design & conduct experiments and analyze & optimize product/process performance using sound statistical techniques.

BODY OF KNOWLEDGE

Introduction to DOE
  • Experimental design
  • Single factor experimentation
  • Factorial notation
  • Controllable & Response variables
  • Planning for DOE
  • Interactions

DOE Design

  • One Factor Experiments
  • Full factorial & Fractional factorial designs
  • Confounding
  • Resolution
  • Repeats and Replicates
  • Randomization & Blocking

DOE Analysis

  • Practical , Graphical and Analytical approaches
  • Main effects and Interaction effects
  • Diagnostic plots
  • ANOVA Model
  • Multiple regression model
  • Response optimization
  • Using MiniTab for Analysis and optimization
Case study presentations
Work Practice (Class room exercise)

Taguchi Methods

  • Robustness & Noise
  • Parameter design
  • Orthogonal Arrays
  • Selection of Orthoganal arrays
  • Signal to Noise Ratio (S/N)
  • Analyzing Taguchi designs
  • Optimization
Exercises on MiniTab
Response Surface Designs
Multi response optimization – Grey Relational analysis

TRAINING METHODOLOGY

  • Lecture & Presentations
  • Worked examples
  • Case studies
  • Work practice
  • Practice on MiniTab Statistical software