Predictive analytics systems leverage AI to foresee potential machine breakdowns before they happen, enabling proactive maintenance and optimized operations. Predictive analysis enables users to utilize bite-sized chunks of big data to predict the future behaviour of machines. Historical data provides insights from past events, like machine breakdowns, to inform future actions.
Goals include increased efficiency, reduced inventory management costs, and improved machine operating rates.
Development of OMNI edge
THK, Inc. developed the OMNI edge as an advanced predictive analytics system. The system employs a secure communications network to analyze real-time data of machine components and perform predictive failure detection. It leverages artificial intelligence to explore historical data, identify patterns, and predict future events, thereby answering the crucial question, “What’s going to happen next?”
The OMNI edge technology uses sophisticated algorithms and reference data to quantify the status of components, monitor their condition, and detect part failures before they occur. This results in increased machine uptime and optimal operation. The overall objectives are to enhance maintenance efficiency, lower inventory management costs, and boost machine operating rates.
Why and How Was the OMNI Edge Predictive Analytics System Developed?
With the advent of 5G and 6G technologies, automation and robotization will advance significantly within Industry 4.0 environments. The ability to achieve predictive failure detection and implement preventative measures swiftly will be crucial as machine interconnectivity grows.
A key feature of OMNI edge is its versatility; it can be installed on both new machines and existing ones that customers are currently concerned about. This flexibility, combined with the capacity to gather and analyze large volumes of data, not only enhances the service but also aids in the development of new products and upgrades.
Machine Issues Identified by OMNI edge
- Linear Motion Systems
- Rotary Equipment
- Cutting Tools
Using AI to Predict “What’s Going to Happen Next?”
Linear Motion Systems
Rotary Equipment
- Alert when an abnormality is detected
- Predicted failure mode
- Maintenance recommendation
- Diagnostic
Cutting Tools
Extensive Reference Data in OMNI edge
OMNI edge uses comprehensive reference data to quantify the status of components. This data is essential for monitoring conditions and predicting failures. The reference data is developed through rigorous data collection and analysis, ensuring high accuracy in predictive maintenance.
- Linear Motion Systems
- Rotary Equipment
- Cutting Tools
Reducing Inventory Management Costs with OMNI edge
Traditionally, MRO (Maintenance, Repair, and Operations) parts inventory faces challenges of overstocking, due to the fear of unexpected failures, or understocking, which can halt production lines. Both scenarios lead to excessive costs. OMNI edge helps users predict the failure of machine components, allowing for optimized inventory management. Users can thus manage their MRO parts inventory more effectively by determining the optimal inventory quantity and timing for procurement.
