Online Course in the Design of Experiments with Minitab

By Gemma Creagh - Last update

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SQT Training are delivering a special online course on the Design of Experiments with Minitab. This virtual course with a duration of 5 half days gives a Course Qualification of Certificate of Attendance. 

Many experimenters are using an OFAT (one-factor-at-a-time) approach to their experimental designs.  In addition to the issue of inefficiency, this approach fails to identify often crucially important interaction effects among factors.  There are available to experimenters advanced analytical tools based on mathematical techniques and utilising special computer software, which will enable them to gain a deep understanding of their processes, including the impact of interactions among factors, and to do so in the most efficient manner with minimum numbers of experimental runs.  These modern DOE tools will be presented on this training course.

  • Duration: 3 training days
  • Course Times: 9.00am – 5.00pm
  • Price: Price: €1150
  • Delivery Mode: This programme is available In-House, on certain Public dates and via Virtual Training

Design of Experiments with Minitab

Day 1

Introduction to Statistics Underlying Experimental Design

  • Mean, variance, standard deviation, degrees of freedom
  • The normal, Student-t and F distributions
  • Normal probability plots
  • Hypothesis testing

Day 2

DOE Terminology

  • Definition of terms such as independent and dependent variables, factors and levels, response, treatment, error and replication

Planning and Organising Experiments

  • Applying the basic elements of experiment planning and organising, including determining the experiment objective; selecting factors, responses, and measurement methods; choosing the appropriate design
  • Design Principles
  • Applying the principles of power and sample size, balance, replication, order, efficiency, randomisation and blocking, interaction, and confounding

Design and Analysis of Factorial Experiments

  • Constructing full-factorial designs and applying computational and graphical methods to analyse and evaluate the significance of results
  • Planning the experiment and determining the experimental objective.
  • Explanation of the terminology – responses, factors, levels, replication, randomization, design points, design runs
  • Understanding the statistical importance of avoiding excess variation in experiments – the role of measurement and careful control of the experiments
  • Establishing the basic principles with a two factor and three factor design – explanation of main effects and interactions
  • Analysis of experimental results using the two-sample t-test, ANOVA, and the probability plot
  • Screening out the non-significant factors
  • Understanding how to interpret interaction plots
  • The role of blocking in DOE
  • The need to reduce the number of runs when there are a large number of factors involved – the concept of using fractional factorial designs

Day 3

  • Fractional factorial designs continued
  • Simple and multiple regression and correlation analysis
  • Analysis of residuals
  • Optimization – Response Surface Methodology (RSM)– Modelling the relationship between factors and responses using advanced mathematical techniques and computer software
  • Simultaneously optimising multiple responses

Who should participate?

  • Product design and process design engineers and scientists
  • R&D engineers and scientists
  • QC and QA personnel

Find out more or register for this course online here.

Gemma Creagh

Pitman Training Naas & Maynooth – Providing Online Training for Career Development
SQT Training: Train the Trainer – Transition to Virtual Delivery


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