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 Data Analysis with Minitab course in advance of attending Design of Experiments.
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.
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.
Upon completion, participants will understand:
- 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. In summary, this approach is useful to anyone charged with optimizing the performance of a process that has many input variables..
· Introduction to Minitab
· Measurement systems analysis (MSA)
· Pre experimental techniques: main effects and regression analysis
· Introduction to DOE
· Designing a simple full factorial experiment
· Factor selection
· Corner points in DPE design
· Running a simple experiment – Catapult simulation
|09:30 – 12:30|
|2||· Analysing and experiment graphically
· Statistical analysis of DOE experiments
· A mug’s guide to DOE ANOVA analysis
· Assignment 1 of 2: multiple choice questions
|09:30 – 12:30||Multiple choice quiz|
· Fractional factorial DOE
· Aliasing in DOE
· Resolution III & IV experiments
· Contour plots
· Dealing with curvature
· Assignment 2 of 2: Fractional factorial DOE case study, using an online simulation tool
|09:30 – 12:30||Multiple choice quiz|
|4||All day live streamed DOE on a moulding machine, from First Polymer Training Skillnet Training Centre in Athlone. Theory interval in the afternoon, covering.
· Multiple response DOE
· Evolutionary operations (EVOP)
· Response surface methodology (RSM)
|09:30 – 17:00|
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).
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.