Predictive Maintenance

The factory floor’s use of machine learning and artificial intelligence (AI) is still being fully tapped by manufacturers.

The essential tasks of AI in manufacturing today go beyond robotics and automation; they also involve enhancing processes, boosting overall equipment effectiveness (OEE), and playing a crucial part in predictive maintenance.

Predictive and preventive maintenance are sometimes confused, but they differ in important ways.

Machine learning principles are used by artificial intelligence (AI) to address a wide range of service-related issues.

Automation and the development of analytics models by machine learning can provide your service staff the tools they need to take preventative action and stop any downtime before it even happens.

Machine learning and artificial intelligence are dynamic systems that improve as they are exposed to more data.

Overall Equipment Effectiveness (OEE)

  • To optimize overall equipment effectiveness (OEE), AI offers thorough analysis.
  • Artificial intelligence (AI) is used to monitor and detect quality problems or missing materials in production control, enabling automatic failure notification warnings.
  • This enables manufacturers to lessen the impact of such failures and preserve high-performance assets.

Defect Detection

  • Through intelligent vision systems and video analytics technology, AI automates defect identification.
  • A vision system efficiently and accurately detects misaligned parts as well as missing or incorrect components.
  • This vastly raises the caliber of the produced goods.

Defect Detection

  • Through intelligent vision systems and video analytics technology, AI automates defect identification.
  • A vision system efficiently and accurately detects misaligned parts as well as missing or incorrect components.
  • This vastly raises the caliber of the produced goods.

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