In today’s fast-paced industrial environment, keeping critical machines running smoothly is essential. edgeRX solutions help manufacturers and distributors achieve industry 5.0 by reducing maintenance-related costs and providing real-time visibility into machine health.
Advanced Machine Health Monitoring with edgeRX
edgeRX is an advanced AI-driven solution designed to revolutionize industrial equipment monitoring and maintenance. By leveraging innovative edge AI and sensor technology, edgeRX provides real-time insights into machine health. This ensures optimal performance and significantly reduces unplanned downtime.
Benefits of edgeRX include:
- Increased Asset Lifespan
- Efficient Technician/Resource Allocation
- Improved Safety
- Reduced Unplanned Downtime
The Cost of Unplanned Downtime
In industrial manufacturing, unplanned downtime can be incredibly costly. Expenses related to electricity, labor, and production output loss can amount to billions of dollars annually. Inefficient maintenance processes often lead to extensive repair times and high costs. This is compounded by oversupply of spare parts, reliance on manual data collection, and inconsistent technician support.
Consider a motor in a manufacturing system. A company using a ‘Run-to-Failure’ maintenance strategy may have several technicians on standby to monitor or repair the motor if it breaks down. However, the motor might operate alongside other machines like pumps and reciprocating machines. When the motor fails, technicians may need to diagnose these other machines to pinpoint the failure, slowing or halting production.
See below for a quick overview for each component in the edgeRX ecosystem.
The edgeRX Platform
The edgeRX platform includes sensors, gateways, and machine learning AI that is fully automated in the cloud backend. Here’s how it works:
- Data Collection: TDK SensEI experts assess the manufacturing environment and recommend sensor placement for data collection. If data collection is already being done by the user, edgeRX AI can adapt and refine models to integrate its learnings.
- Model Generation: Collected data is analyzed and fed into trained AI models to determine the operational or ‘healthy’ state of a machine. When degradation or failure occurs, it is flagged as an anomaly. edgeRX AI can perform multi-class anomaly detection, accurately identifying different fault states (e.g., looseness, cavitation). When issues are detected, the sensor sends a warning to a gateway device which in turn alerts the system for potential issues.
- Model Deployment: Within 1-2 weeks, data collection is automated. A trained AI model can be installed onto a sensor (the edge). The capability of the deployed model will increase over time as it acclimates and learns about its environment.
- Advanced Condition-Based Monitoring (CbM)
- edgeRX employs condition-based monitoring (CbM) as its first phase of machine maintenance. edgeRX AI can detect faulty states beyond standard ISO frameworks, providing users with deeper insights into their machines’ performance. CbM informs where machines break down in an environment, giving technicians fast diagnostics and accuracy. See our case study where edgeRX reduced annual unplanned downtime costs by $192 million for an elevator company.
- Predictive Maintenance:
- As condition-based monitoring continues to develop, models within sensors will be able to detect upcoming machine failures or maintenance needs. This can be early warning signs for faulty parts, imminent breakdowns, or recommendations for maintenance supplies and routine checkups. Users will be able to adjust forecasts to their desired sensitivity.
Interested? Fill out the form below to see how TDK SensEI’s edgeRX solution can help you reduce unplanned downtime.