AI FOR FOUNDRIES


Learn how A.I. helped a major engine block manufacturer attain zero percent external scrap.

Join us at GIFA where our partners, Pour-Tech will be showcasing our AI for manufacturing solution.

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CLIENTS

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“I have been using your prescriptive reports to make small calculated adjustments to our system. The norm for us is 5-6% internal scrap and 10-15% rework. Over a two day period we managed to achieve 1% internal scrap and 8% rework. In the past we have been able to achieve similar results, but we had absolutely no clue what we did to achieve the good result. This time around we have a fairly good idea of what we did to achieve the result. Thanks for your tremendous efforts and help to take us to the next level.”

Chief Executive Officer

IMPROVE OUTPUT IN FOUNDRIES WITH INDUSTRY 4.0

The world is evolving ever more rapidly and the foundry industry is no exception, data is at the heart of the fourth industrial revolution. Often stored in disparate sources across a plant, timely analysis and actionable insights are key to unlocking the immense value encoded in plant measurements. The application of these prescriptive actions is used to achieve the optimal state of production and improve output in foundries. Artificial Intelligence (AI) is the innovation that makes this possible.

2% total business costs saved with no process changes

0% external scrap

4-6 week deployment


Through numerous implementations of our AI solution, DataProphet has provided clients with expert advice proven to deliver actionable and measurable results for continuous improvement in plant operations. This is the realisation of the Industry 4.0 vision in foundries.

DataProphet’s team of highly skilled engineers and data scientists partner with clients to gain a thorough understanding of the processes within the plant, identifying relevant data sources and mapping the data environment in the context of the physical plant. DataProphet builds a unified view, linking both quality and process data. Upon ingestion of the data, our AI solution identifies an optimum operating paradigm to reduce variation and prescribes actions to achieve the optimal yield, resulting in more predictable plant performance.

  • 12 months to five years historic data analyzed

  • 5% production increase

  • Product traceability

  • 1m+ records and 100,000+ unique features in single view

CASE STUDIES


MANUFACTURING CASE STUDY

Predicting engine block defects and identifying high yield operating regions.

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PRODUCT SHEET

$400,000 monthly savings and 0% defects on shipments.

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COMPUTER VISION CASE STUDY

Machine vision systems for enhanced quality control.

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