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Quality by Design (QBD) and Design Space – Web Course

Quality by Design (QBD) and Design Space – Web Course


Design of Experiments (DOE) is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using only the minimum of resources. DOE is the backbone for efficient QBD implementation strategies. The final specifications for a region where all specifications are fulfilled to a defined risk level is called Design Space. The course is composed of lectures, demonstrations and computer exercises in software MODDE® based on real life investigations. We always strive to deliver great training with focus on the participants and the learning capacity. To ensure a good training quality, the trainings are split over five sessions. One home exercise per session is included and it is expected that the course delegates work on each exercise outside the session time.


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.


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.


  • 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


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


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 Set Point
  • Proven Acceptable Ranges
  • Software click-along demo
  • One home exercise
  • Course debfriefing and final Q&A


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


We recommend to listen to “Design of experiments (DOE) for the beginner” before course start (watch recording).

If you have any questions, please do not hesitate to send an e-mail to:


Cancellations received later than two weeks before the course starts 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.

Course participant(s) can be substituted by the registering company as long as Sartorius Stedim Data Analytics AB is notified.

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

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