This is a continuation of Predictive Analytics - Solve a Critical Quality Problem. A BioPharmaceutical Manufacturing company was scrapping about 30% of batches, which is very expensive. The company's engineers tried to solve the problem with various techiques.
But it was not until they started using predictive analytics (also know as data mining) that they uncovered actionable process improvements. These improvements are predicted to lower the scrap rate from around 30% to 5%.
How were these improvements discovered?
Recently, my colleagues and I worked with a BioPharmaceutical Manufacturing company to apply predictive analytics methods to solve a critical product quality problem. We were looking for root cause(s) of this complex problem.
The company manufactures vaccines under strict regulatory guidelines for sterile manufacturing and packaging environments.
The Problem: Specifically, in an important part of the process in which they manufacture one of the active ingredients for a vaccine, they were scrapping about 30% of batches.
Conservatively, scrap at this level resulted in millions of dollars