AI for the Automotive Industry


Learn how Artificial Intelligence (AI) can be used to optimize production in the automotive industry and achieve operational targets.

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The impact of AI on the automotive sector


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Improve output in the automotive sector with industry 4.0


Artificial Intelligence (AI) and Machine Learning can help both vehicle parts suppliers and vehicle assembly lines to improve key plant metrics, reduce downtime, rework and scrap. DataProphet can achieve this without additional hardware requirements, using only data that you already own.

Today’s vehicle manufacturers rely upon Just In Time (JIT) production systems that are lean by definition. These are typically characterized by:

  • A critical need to preserve supply chain logistics,
  • No tolerance for defects, errors, or repairs, and
  • The use of performance penalties to recover from the impact of a defect on these inflexible lines.

Reduce defects and variance in quality


Using only data
you already own

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2%
Total Business Costs Saved with no process changes
0%
External Scrap
4 - 8
Week Deployment
1 - 5 Years
Historic data analyzed
5%
Production Increase
Assembly Validation
>700M records
5 - 10k features
In a single view

DataProphet's Automotive Solutions


DataProphet’s solutions can optimise your manufacturing process, preventing defects from occurring in the first place. The AI at the heart of DataProphet PRESCRIBE learns and then prescribes the combinations of materials, process parameters and other conditions that result in a higher yield. In this way DataProphet steers the manufacturing process into an operating region that:

  • Lowers the cost of non-quality
  • Increases efficiency
  • Provides higher yield

Based on historical production data, DataProphet PRESCRIBE accurately predicts the presence of defects. It does so by recognizing patterns that have previously been associated with one or more known defects. DataProphet can detect defects that you would not otherwise be directly aware of, such as:

  • Subsurface defects
  • Latent defects (particularly important where warranty claims could be significant)
  • Uncaught quality violations
  • Hidden scrap

Traditionally, the cost of detecting these types of defects has been high, especially when considering:

  • Shipping
  • Factory downtime
  • Disrupted logistics
  • Customer dissatisfaction

DataProphet PRESCRIBE and DataProphet INSPECT can help manufacturers to find and quarantine bad components before they become costly.

Stud Welding Case Study


55% reduction in stud welding defects.

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Manufacturing Case Study


Predicting engine block defects and identifying high yield operating regions.

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