How Digital Twins and Model Ops Operationalize Data Science for Manufacturing

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.

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Success with TIBCO:

2,000+

Spotfire users

Over $1 million

In projected opportunities

3 Months

Time to learn Spotfire and develop the first analysis model

74 Percent

Fewer surgical site infections

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