A business analytics approach to augment six sigma problem solving: A biopharmaceutical manufacturing case study

Abstract

Biopharmaceutical manufacturers are required to collect extensive observational data sets in order to meet regulatory and process quality monitoring requirements. These datasets contain information that may improve the performance of the production process. Analytics provides a means of extracting this information while Six Sigma provides a means for the insights to be incorporated into production practices. We present a novel framework which combines Six Sigma and Business Analytics. This approach mines large volumes of inline and offline biopharmaceutical production data, allowing the entire production process to be analysed and modeled. The recommendations of the model are represented as manufacturing rules which give actionable insights to improve the performance of the process. The integrated approach delivers promising results from synthetic experiments as well as being applied in practice to a cell culture process.