Tolerating Input Variation: How to Design for Robust Production Processes

When transferring products and processes from development to routine manufacturing, one major challenge is often ensuring that the process tolerates a wide variation of critical inputs, such as material. This makes it easier for manufacturing to sustain consistently high product quality and allows greater flexibility when adapting the process in the future as circumstances change that are beyond our control.  

In this webinar, scientists and engineers in the pharmaceutical and other highly regulated process industries will learn strategies and techniques on how to design new products, develop new processes, improve existing processes so that they can tolerate as much variation as possible in incoming material, processing, and operating characteristics. 

You will learn how to:

• Reduce development time with design of experiments and quality by design.
• Use data analysis to optimise a process or system for maximum quality at minimum cost.
• Adapt a process to account for changes in material or process input.

Owen Jonathan is an Associate Systems Engineer for JMP Statistical Discovery, which creates interactive and highly visual statistical discovery software for scientists and engineers. His role involves identifying critical business issues of customers in the UK and guiding them as they adopt data-driven solutions for their organizations. Owen has a master’s in systems and synthetic biology from Imperial College London. Prior to becoming an SE, Owen joined JMP as an intern where he identified design of experiments (DOE) applications in the field of biotechnology and delivered DOE workshops with relevant case studies to synthetic biologists.