Scaling automotive rubber optimization for the digital era
Top tire maker achieves scalable, peak manufacturing efficiency with data-driven prescriptive AI.
quality metrics improved
%
average overall improvement
The context
A world-leading tire manufacturer engaged Dataprophet to guide them in optimizing its rubber mixing process. This automotive OEM wanted a data-to-value solution that could optimize key processes at scale for the digital manufacturing era.
The customer aimed to improve six quality metrics on two automotive tire product lines simultaneously using obfuscated data.
The results
Advanced data analysis methods revealed multiple best-of-best (BOB) operating regions. Contextualizing these operating regimes crystallized optimals based on a particular plant state over time while safeguarding proprietary process knowledge.
The tire manufacturer simultaneously optimized six target quality metrics for a 39% average improvement while adapting to variations in weather and raw material properties.
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