Digital Twin Simulation for Predictive Industrial Maintenance
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Solution Overview
Problem
Current digital modeling technologies lack effective methods for predicting and prioritizing preventative measures and maintenance in industrial settings, such as shop floors, where events like static electricity generation, leaks, and accidents can occur, leading to potential damage and operational disruptions.
Innovation Solution
A system utilizing digital twin simulations to generate predictions and determine mitigation procedures by obtaining digital replica models of equipment, receiving data feeds, simulating operations, and predicting events, thereby enabling proactive maintenance and prevention strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital replica models and simulations are implemented to predict events and determine mitigation procedures, then reliability and safety of industrial operations are improved, but device complexity and implementation cost increase
Solution Approach 1:
The patent creates digital replica models (digital twins) that are virtual copies of physical equipment, processes, and systems. These digital replicas mirror the physical entities' behavior, parameters, and operational characteristics, enabling simulation and prediction without requiring physical experimentation or complex physical modifications to the actual equipment.
Solution Approach 2:
The system performs simulations and event predictions in advance before actual events occur. By using the digital replica to model future scenarios, identify potential failures, and determine mitigation procedures proactively, the system enables preventive maintenance and operational adjustments before real-world problems manifest, improving reliability while managing complexity through virtual rather than physical intervention.
2Measurement precision
If continuous data feeds are collected from equipment to improve simulation accuracy, then measurement precision and prediction quality are improved, but loss of time for data processing and system response increases
Solution Approach 1:
The patent implements continuous data collection from physical equipment through sensors and data feeds, which are fed into the digital replica model. The simulation system processes this data to generate predictions and mitigation recommendations, which are then fed back to operators or automatically implemented. This closed-loop feedback system maintains high measurement precision by continuously updating the digital replica with current equipment state data while managing processing time through efficient simulation algorithms.
Data Source
AI summary
Methods, computer program products and/or systems are provided that perform the following operations: obtaining digital replica models for equipment at an industrial location; receiving data feeds associated with the equipment; simulating operations of the equipment based on the digital replica models and the data feeds; predicting one or more events associated with areas within the industrial location based, at least in part, on the simulating of operations of the equipment; and determining one or more mitigation procedures based on the one or more predicted events.