Today's increasingly technologically sophisticated equipment enables AI to reliably predict potential issues, giving you the ability to proactively address a failure before it has a major impact on operations.
Conventional Preventive Maintenance | Predictive Maintenance | |
---|---|---|
Regular Inspection Work | Done Manually | Automated by the system |
Inspection Method | Lines had to stop to perform inspections | No line-stop required, continuous monitoring |
Evaluation Criteria | Difficult to assess suspect parts without data | Uses machine learning with concrete vibration, temperature and noise data |
Accuracy | Quality of maintenance outcomes depends on the judgment and experience of service technician | Improved accuracy based on quantitative AI data analytics |
Quality of Work | Part replacement workmanship depended on a manual checklist | Sensors detect minor defects in workmanship |
Sudden Machine Trouble | Sudden machine trouble depended on the inspection cycle | With continuous monitoring, sudden machine trouble is zero |
Overlooking subtle changes in vibration of equipment is not an option!
Fluctuations in data are analyzed by AI to signify potential failures and issue an alert.
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