Preventive maintenance inspections are a critical part of any successful condition monitoring program. Yet traditional manual inspections can be time consuming, costly, error prone and occasionally dangerous.
As cameras, audio sensors, drones and unmanned vehicles begin to take the place of hands-on technician visits — especially in dangerous environments — pioneering organizations are using artificial intelligence (AI) techniques to inspect equipment. These organizations are able to safely limit wasted effort from unnecessary in-person inspections, reduce inspection times, address skills gaps, and improve the consistency of identifying problems that can result in downtime.
Key capabilities of Visual Insights
Machine learning for visual feature extraction
Edge processing for rapid image acquisition and processing
Confidence levels for more accurate and automated defect identification
AI for continual improvements in detection and recognition accuracy
Tune up inspections with Acoustic Insights
Identify problems faster and more consistently
Manufacturers are using acoustic pattern recognition technology with AI-powered insights to non-destructively and non-intrusively improve quality and prevent costly equipment downtime. This frees inspectors from manual methods that require time and experience to master. When Acoustic Insights is deployed on the factory floor, it can identify audible and inaudible sounds related to equipment failure and suggest maintenance.
The use of AI in preventative maintenance can reduce inspection times and costs while increasing accuracy and consistency, which helps improve the productivity and performance of maintenance teams.
Key capabilities of Acoustic Insights
AI algorithms for real-time acoustic recognition from unstructured data
Continual defect model improvement for increased accuracy over time
Sound pattern recognition for non-destructive identification and monitoring
Acoustic pattern analysis for early detection of equipment degradation
Transform inspections with IBM Maximo PQI – Visual Insights
Inspection time and cost reduction
Detects issues with image recognition technology fast using AI-powered visual inspection techniques, helping to automate the inspection process and reducing the need for manual in-person inspections.
Inspection process reliability improvement
Identifies problems that the human eye can’t and classifies issues using confidence thresholds to help improve consistency and accuracy of defect identification when compared to manual approaches.
Health and safety improvement
Uses image recognition technology to reach places that humans cannot safely inspect, so inspectors can stay out of dangerous environments.
Inspection training time reduction
Reduces the need for costly and time-consuming inspection training while reducing the impact from inspector churn by centrally capturing problem classification and root-cause identification.
Tune up inspections with IBM Maximo PQI – Acoustic Insights
Real-time acoustic recognition
Identifies sound and vibration patterns from unstructured acoustic data using deep-learning AI algorithms, while being trained in the cloud to identify anomalies, defects and maintenance issues.
Early detection of equipment degradation
Detects subtle signs of equipment degradation or malfunction and uses acoustic patterns to identify the root-cause and suggest maintenance well before damage becomes an expensive problem.
Employs sound pattern recognition, which is non-destructive, so you can identify, monitor and proactively remedy issues when environmental or physical obstructions make it difficult to observe tests.
Defect model creation
Combines machine learning based on curated acoustic recordings of defects and human knowledge to create a defect library that can be deployed to automate quality inspections and diagnostic analysis.
Learn more about Visual Insights and Acoustic Insights