Manufacturing Case Study: Foundry

Our client is one of the largest foundries in the Southern Hemisphere. Each year it produces 129,000 high-quality cast iron automotive components, or over 46,000 tonnes, at its plant. The plant has an annual melting capacity of 110,000 tonnes. In order to compete globally and to achieve its vision to be the best foundry in the world, our client embraced the opportunities of Industry 4.0. As a result, it has become one of the most innovative and advanced foundries in the world.

They “embraced the information flow and sharing principles that underscore what is commonly referred to as Industry 4.0,” our client explained. “We upgraded and increased digitization and the acquisition of information across all stages of production. A natural outcome of this strategy was to use the production and quality data to enable plant engineers and managers to make better, more informed decisions.”


Our client wanted to find a way to optimize its manufacturing process to reduce the cost of scrap. While the scrap rate was no higher than the industry standard, every defective unit shipped and scrapped in Europe or North America incurred a relatively high shipping cost.

The main objective was therefore to lower the number of defective engine blocks shipped, by reducing the internal and external defect and scrap rates. In turn, this would increase production, and reduce rework.
This is not a novel objective for many plant managers and process engineers across the world. The challenge, historically, is in the level of complexity in the large number of non-linear causal relationships that make up the modern foundry.




Too often, AI-as-a-Service providers equate research-based methodologies with one-size-fits-all industry solutions. DataProphet works closely with partners to gain an understanding of their unique set of production problems. We adopt AI-driven manufacturing solutions to the production dynamics of your factory floor, incorporating our proven, industrial process expertise, but taking our cues from contextualized feedback. We understand that most impact is achieved by building machine-learning models to mesh with your production lines' realities and the assets that drive them. Our partnerships are guaranteed win-win.

Production Increase

Product Traceability

0% External Scrap

Guaranteed ROI