Empowering operators with actionable prescriptions for continual improvement
Our customer is one of the world’s leading manufacturers of a wide range of high-quality, light-alloy wheels for premium vehicles. This global automotive OEM prides itself on excellence, innovation, adaptiveness, reliability, and the technical upskilling of its teams. Aligned with the new era of data-driven production, the company is also fully committed to eliminating manufacturing errors in the spirit of continuous improvement.
DataProphet PRESCRIBE—our flagship AI-driven process optimization solution—was deployed at this automotive OEM to reduce scrap produced during its light-alloy wheel manufacturing process.
‘Hot’ (i.e., visual) scrap—from manual inspection of wheels just out of the casting furnace—constituted the bulk of casting defects for this automotive OEM. Reducing them would mean significant savings from needless value-adding to a product that would later fail downstream inspection.
The wheel maker determined that X-ray scrap further down the line also warranted scrap reduction.
Therefore, DataProphet agreed to target the reduction of both “hot” and X-ray scrap.
By overlaying historical and actual quality and process data, PRESCRIBE’s model works to automate the update loop of the control plan for continuous improvement. What this looks like for operators is a prioritized list of easily actionable prescriptions timeously delivered to a dashboard. Enacting the prescriptions moves production closer to its best-of-best (BOB) operating region.
DataProphet built a data collection system that enabled high-resolution monitoring and contextualization of process data and quality data. This system linked to the controllable parameters deemed by our prescriptive AI to have the highest impact on scrap reduction.
Namely, pre-emptive, dynamic prescriptions were generated for furnace pressure, die temperature, ON/OFF times of cooling channels in the die, metal temperature, metal fill-up temperature, plant temperature, and compressed air.
During the commissioning test, factory operators adhered to the critically important compliance level of 80+% for one of the two targeted wheels. These adjustments to the control plan resulted in a 29% reduction of scrap for this wheel.
It is projected that if DataProphet PRESCRIBE were deployed to all products and furnaces at the site—a gross annual saving for the plant of more than €0.5m and a production volume increase of 2.4% would be achieved.
The data discovery journey itself added significant value to the plant’s standard operating procedure. This was achieved by refining the data, improving logging resolution, logging additional parameters, and implementing a more traceable and reliable method of recording visual scrap.
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