LEADER IN AI THAT ENABLES AUTONOMOUS MANUFACTURING
SCALING AUTOMOTIVE RUBBER OPTIMIZATION FOR THE DIGITAL ERA
A world-leading tire manufacturer engaged DataProphet to optimize its rubber mixing process. This automotive OEM wanted a data-to-value solution that could optimize its processes at scale for the digital manufacturing era. The project aimed to determine two products’ peak rubber mixing process efficiency.
The automotive rubber manufacturer optimized six target quality metrics simultaneously, drawing on the core capabilities of functional manufacturing expertise and data science.
ADAPTING OUR SOLUTION TO MEET CUSTOMER NEEDS
DataProphet adapted its techniques by analyzing and modeling the factory’s historical process and quality data statically. Advanced data analysis methods revealed multiple best-of-best (BOB) operating regions. Contextualizing these operating regimes crystallized optimal based on a particular plant state over time.
RESULTS
With this collaborative solution, plant engineers now have the insights to leverage their rubber manufacturing process knowledge with high-quality data.
PARTNERING FOR DIGITAL-ERA MOMENTUM
The next step is systematically scaling the data-driven insights and learnings across the customer’s other rubber manufacturing plants.
“We are very excited to be part of the fast rollout journey with this tire manufacturing partner. As a group, we believe our insights from the use case can greatly impact the quality outcomes of this next phase at scale.” Renita Raidoo (project team member and DataProphet data scientist).
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