The power of structured experimentation in science and engineering
Fast-Track Innovation and Process Improvement
“Products and processes are perhaps more complex than ever,” says Peter Goos, Professor at University of Leuven and co-author of Optimal Design of Experiments. This means we have to engage in “hard work, many tests, substantial experimentation. Subject matter expertise alone will usually not suffice to optimize these highly complex products and processes.”
Through a series of case studies, Goos demonstrates how design of experiments (DOE) can be used to successfully drive the performance and quality of products and processes.
Watch to learn more about:
- The weaknesses of one-factor-at-a-time experimentation.
- The key features of properly designed experiments.
- Success stories from companies that have applied DOE in combination with statistical techniques.
Microsoft, Riffyn and Corning use design of experiments to solve problems, create new products
When it comes to solving problems in industrial R&D and manufacturing, we need DOE to gain fundamental knowledge of our systems, processes and products. Once processes are well-defined and predictable, your organization can deliver more confidently on a commercialization timeline. Without this knowledge in an ever-changing world, you run the risk of losing your competitive advantage, profits or business.
How do innovative organizations use DOE for efficient, effective discovery of practical insights?
You’ll hear from:
- Vicky Svidenko, Microsoft
- Timothy Gardner, Riffyn
- Michael Anderson, Corning
- Bradley Jones, JMP