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Description

This course demonstrates how to meet FDA, automotive and medical device requirements for product and process validation. Discover the techniques that you and your suppliers should implement to ensure incoming materials and products meet your Quality requirements. Provide customers with proof of process capability for both normal and non-normal data.  Use Gage Repeatability & Reproducibility studies to determine measurement system capability and reduce variation, including Attribute Agreement Analysis for visual inspection. Based on Statistical Process Control (SPC) principles, implement the correct control chart and sampling plan for your manufacturing process. This course covers everything a Quality engineer should know in a practical way, as we work through Quality systems from DuPont, Kraft Foods, Restek, Bayer, Goodyear Tire, Smith & Nephew, Harley Davidson, and more.

You’ll learn the SPC, Process Capability and Gage R&R tools to validate products and processes!

  • Complete understanding of a Standard Gage R&R

  • Attribute Agreement Analysis for visual inspection improvement

  • Gage Run Chart to communicate the results of your study

  • Nelson SPC Rules for identifying special cause variation

  • X bar & R, I – MR, S, p, np, C and U Control Charts

  • Sampling Plans for all Quality tool studies

  • Process Capability for normal and non-normal data

  • Data transformations and Distribution Identification

  • Operator-by-Part Matrix Summary

Peers

Participants include other engineers, technicians and scientists providing a great networking opportunity.

Exclusive

In addition to the workshop, there are three personal 1:1 sessions available with your trainer.

Testimonials

“You can tell the trainer is passionate about his work and it rubs off on the class.  One of the best training facilitators I have had the pleasure to work with.”

“The training uses a good communication model. Theory, practice then work an exercise on our own and review. We did this for each major chapter and it worked really well. Kept my interest!”

“We discovered huge opportunities in our historical data and they had been sitting there for years, right under our nose!  I am excited to move on to my next project and so is my company.”

“ Great class!  I can’t wait to sign up for the next topic.”

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