Design of Experiments (DOE)-Online

Dates: 2nd November, 2020 - 26th November, 2020 (8 days)

Duration: 8 x 2 hour session , twice per week = 16 contact hours total over 4 weeks.

Location: Online

Accreditation: Certificate of attendance

Full Fee: €650

Programme overview

To get the most out of this programme participants should already have a good working knowledge of statistics.  If this is not the case,  we recommend attending our 2 day ‘Process Analysis and Control using Minitab’ course in advance of attending Design of Experiments.

Minitab

If you are not joining from work, or don’t have access to a Minitab licence, students will need to download a trial version of Minitab in advance of the course. If that’s not possible for the student, they can still join in as an observer and commentator.

The opening webinar in the series contains an introduction to Minitab software,and will give an introduction to statistics, using Minitab.

Broadband reliability

Students will need reliable broadband and a quiet place from which to join in. Landline broadband speeds have been affected by the COVID-19 induced demand on streaming services. A landline broadband service should be good enough for a webinar? Using a smartphone hotspot works very well also, if the student has 4G service.

This course is designed for product or process development engineers, technicians, scientists and statisticians in all industries and services including pharmaceutical, medical, automotive, engineering, semiconductor, plastics and composites. DOE is particularly useful for the development of new analytical tests and methods. In summary, this approach is useful to anyone charged with optimizing the performance of a process that has many input variables.

If you are unsure or have any questions, please feel free to contact us.

Learning outcomes

Upon completion, participants will understand:

  • The need for good experiment design
  • How to select relevant factors (process inputs) for DOE
  • How to structure selection of tests to run, to minimise the amount of testing needed
  • How to design and run an experiment
  • How to graph and analyse DOE results
  • How to bring about a significant sustainable process improvement, based on scientific understanding of influencing process inputs.

Who is the course for
The DOE course is suitable for product or process development chemists, engineers, technicians, scientists and statisticians in all industries and services including pharmaceutical, medical, automotive, general engineering, semiconductor, plastics and composites. DOE is also particularly useful for the development of new analytical tests and methods. In summary, this approach is useful to anyone charged with optimizing the performance of a process that has many input variables.

Course content

 Session
Content
Tutor
Hours
Assignment
1
  • Introductions
  • Descriptive statistics
  • Correlation & regression
  • Introduction to DOE
  • Assignment

BR

2

10 questions on descriptive statistics, correlation & regression
2
  • Assignment review
  • Designing a simple full factorial experiment
  • Factor selection
  • Centrepoints & blocking
  • Running a simple experiment – Statapult simulation
  • Assignment

BR

2

Statapult data set exercise

3

  • Assignment review
  • Analysing and experiment graphically
  • Analysing and experiment statistically
  • Assignment

BR

2

10 questions on DOE data sets

4

  • Assignment review
  • Analysing and experiment statistically
  • Fractional factorial DOE
  • Aliasing in DOE
  • Assignment

BR

2

Sample data sets exercise

5

  • Assignment review
  • Contour plots & dealing with curvature
  • Other experimental designs: Placket Burman & EVOP

BR

2

Sample data set exercise

6

  • Assignment review
  • Moulding DOE – process parameters & factor selection & settings
  • Assignment

SOL

2

DOE data exercise

7

  • Assignment review
    Moulding DOE set up in Minitab
  • Case study review
    Assignment

SOL

2

DOE data exercise

8

  • Assignment review
  • Process considerations Q&A
  • Graphical and data analysis of Moulding DOE
  • Assignment

SOL

2

DOE data exercise
Total Hours 16

Trainer Profile

Bernadette Rushe,

Bernie has been involved in the management of supply chain and business process improvement activities for over 30 years. She received her Lean and Six Sigma training at Dell Computer Corporation. In 2001, she left Dell to establish Cordatus Consulting (now trading as Lead Ireland).

Stephen O’Leary 

He graduated from Athlone IT having studied Plastics Engineering from 1988 to 1992. Stephen has delivered training in Injection Moulding for First Polymer Training since 2000, initially joining FPT Skillnet as the Training Center Manager.

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