Two Day Design of Experiments (DOE) for Process Development and Validation Course - Los Angeles, CA, United States - March 30-31, 2017 - Research and Markets

Research and Markets has announced the addition of the "Design of Experiments (DOE) for Process Development and Validation" conference to their offering.

Prior to developing a process control plan as part of an overall risk management strategy, process development studies must be completed. The objective of these process development studies is to gain knowledge and understanding about how variation in process parameters explains variation in the product quality characteristics of the product.

The use of DOE methodology provides a means to identify process parameters which impact product quality (critical process parameters) and determine the functional relationship that links the process parameters to those critical quality attributes. Screening designs, such as 2k factorial and D-optimal designs, are used to determine critical process parameters. Response surface designs, such as Central Composite Designs (CCDs) and I-optimal designs, are used to model the functional relationship between those critical process parameters and the critical quality attributes.

This course will begin by presenting a primer on statistical analysis, focusing on the methods required for analysis of designed experiments. It will then present the steps to DOE, while demonstrating valuable risk management tools (Ishikawa and FMEA) which can be use pre and post DOE studies. Next, participants will learn to generate and analyze multiple screening and response surface designs; the participants will leave with an understanding of why and how each are used. Then, the participants will learn how results of the studies can be presented. Lastly, using the results of the studies, the risk management tools will then be updated.

Who Should Attend:

- Process Scientist/Engineer

- Design Engineer

- Product Development Engineer

- Regulatory/Compliance Professional

- Design Controls Engineer

- Six Sigma Green Belt

- Six Sigma Black Belt

- Continuous Improvement Manager

Agenda:

Day 1 Schedule

Lecture 1: Primer on Statistical Analysis

- Basic statistics

- Two-sample t-test

- ANOVA

- Regression

- Internal Audit is a secret to success

Lecture 2: Introduction to Design of Experiments (DOE)

- Steps to DOE

- Defining critical quality attributes (CQAs)/responses

- Identifying and prioritizing potential process parameters

Lecture 3: Screening Designs

- Full factorial designs

- 2k factorial designs

Day 2 Schedule

Lecture 1: Screening Designs (continued)

- Fractional factorial designs

- D-optimal designs

Lecture 2: Response Surface Designs

- 2k factorial designs with center points

- Central Composite Designs (CCDs)

- Box-Behnken designs

- I-optimal designs

Lecture 3: Utilizing Systematic Understanding from DOE Studies

- Presenting results

- Control plan/risk management strategy

For more information about this conference visit http://www.researchandmarkets.com/research/v89gtc/design_of

View source version on businesswire.com: http://www.businesswire.com/news/home/20161128006051/en/