Quality by Design (QBD) and design space | Web Course

Course Objective

On completion, participants will know how to:

• Create efficient experimental designs to match the objectives.
• Analyze experimental data using sound statistical principles.
• Improve and optimize products and processes.
• Interpret the results to increase understanding.
• Make a risk estimate of the decided settings.
• Understand robust optimization objectives
• Set specifications for normal operations (Design Space)
• Report results in a comprehensive graphical format.

Who Should Participate?

The course is intended for researchers, scientists, and engineers from all sectors of industry and academia. Typical applications include product development, process improvement, optimization, validation, and quality control. No prior knowledge of statistics is assumed.

Selected Course Content

• Understanding the DOE concept
• Data modeling and diagnostics
• Create a solid base for decisions
• Finding the optimal setting
• Quality estimates and robustness evaluation
• Design Space specifications

Language Information

Seminars are given in the language stated. In-depth discussion, course material, and printed material are in English; hence knowledge of English is required.

Schedule

Session 1 (3.5h): Introduction, Full factorial designs.

• Introduction to Sartorius Data Analytics
• Focus on how and when should Design of Experiments be used?
• Problem formulation
• Selection of goals, factors, responses, type of model and design
• Properties and analysis of Full factorial designs
• Software click-along demo
• One home exercise

Session 2 (3.5h): Analysis of data, Screening

• Introduction to Fractional factorial designs
• Evaluation of raw data
• Regression analysis and model interpretation
• Screening designs, which factors dominate, and what are their optimal ranges?
• Software click-along demo
• One home exercise

Session 3 (3.5h): Causes of Bad Models, Post Screening actions

• Regression analysis and model tuning to get better models
• What to do after screening, optimization, or modification of the design
• Software click-along demo
• One home exercise

Session 4 (3.5): Optimization, Extra Exercise time

• Introduction to optimization designs
• MODDE optimization tool
• Software click-along demo
• One home exercise

Session 5 (4.5h): (only for QBD delegates)

• Introduction to QBD and design space
• Introduction to Robustness testing
• In-Depth Session on Design Space
• Optimal vs Robust SetPoint
• Proven Acceptable Ranges
• Software click-along demo
• One home exercise
• Course debriefing and final Q&A

Course Material and Software

The electronic course material (course slides and exercises) and the course license will be emailed two weeks before the course starts. MODDE needs admin rights to be installed, so please get in touch with IT soonest. Sartorius cannot help you to install MODDE. We recommend you have two screens or one projector and one PC to follow the course and demos easily. However, this is not required.

Preparation

We recommend listening to “Design of experiments (DOE) for the beginner” before the course start (watch recording). If you have any questions, please do not hesitate to send an email to: umetrics_academy@sartorius.com

Cost and Conditions

The course fee is 2170€ per person.

Cancellations received later than two weeks before the course will not be refunded. For courses cancelled more than two weeks before the course starts, Sartorius Stedim Data Analytics AB will retain 10% of the course fee to cover administrative costs, and the rest of the amount will be refunded.

The registering company can substitute course participant(s) as long as Sartorius Stedim Data Analytics AB is notified.

Sartorius Stedim Data Analytics AB provides courses based on a sufficient number of registrants. Therefore, Sartorius Stedim Data Analytics AB reserves the right to cancel the course 14 days before the course start date if the number of registrants is too low. A full refund will be made to these registrants. A 10% discount will be made to any registrant(s) enrolling in the next available course.