Determining the control strategy for a manufacturing process

How can you determine what control strategy to use for a manufacturing process?
What can you learn from this even if you are not working with manufacturing?

A control strategy for a drug manufacturing process is the overall approach to ensure that when you make the drug product, it’s going to be of acceptable quality. It is a great way to think about how you can optimize and control a very long process that has many factors.

The topics we discuss apply a lot for any other process that you are looking into where there many steps and where understand variability and what is driving quality is important.

In this episode, you will also learn about the design of factorial experiments.

Even if you are not working with manufacturing, you can still learn a lot.

Join Sam and I while we discuss the processes of determining the right control strategy for a manufacturing process:

  • How to determine the control strategy for the manufacturing process?
  • How to demonstrate the characteristics of control strategy?
  • What is the process flow that works?
  • How does a complex system work?
  • How to understand and optimize control strategy?

Sam Gardner

Sam holds a BS in Mathematics and Chemistry from Purdue University, a MS in Mathematics from Creighton University, and a MS in Statistics from the University of Kentucky.

Sam has held numerous roles in his career. Right out of college, he earned a commission as an officer in the United States Air Force. For 12 years, he worked as a military scientific analyst in several roles, including weapon systems modeling and simulation, flight test planning and data analysis, and human factors research and development. He was also a member of the faculty at the Air Force Institute of Technology, where he taught statistics and experimental design to fellow officers in the graduate engineering, science, and logistics programs. 

After three decades of work in government and industry, Sam decided to launch his own business to provide consulting services that utilize his talents in statistical thinking, problem solving, experimental design, and statistics and predictive modeling. 

Sam is a member of the American Statistical Association, the International Statistical Engineering Association, the American Association or Pharmaceutical Sciences, and he also serves as a volunteer member of the United States Pharmacopoeia’s Statistics Expert Committee.  

Sam lives in Lafayette, Indiana, USA, with his wife, Susan, and together they have four adult children.

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