Manufacturers are increasingly turning to digital twins to deal with the petabytes of data generated daily by sensors in their manufacturing process. Traditional, knowledge-driven analysis no longer satisfies business requirements, resulting in lost opportunity, suboptimal product yield, and lowered revenue. However, getting the data science (machine learning models) behind the digital twins into production has proven difficult. That's why TIBCO introduced a Model Ops solution to help companies develop and deploy working and successful digital twin models along with data science.
In this paper, we walk through how one semiconductor manufacturer successfully used the TIBCO Model Ops solution to operationalize data science. The company was able to use the process to produce actionable insights and optimize its manufacturing processes with digital twin models.