Measurement Point Monitoring via Load-Based Failure Prediction
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Solution Overview
Problem
Existing field devices in industrial systems, especially those using analog communication channels, lack predictive maintenance capabilities, leading to unexpected failures and increased downtime due to the absence of real-time error detection for impending issues.
Innovation Solution
A method to calculate and predict the degree of load on field devices and system components by using production and environmental data, allowing for proactive maintenance notifications when thresholds are reached, thereby anticipating and addressing potential failures before they occur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If field devices use analog communication channels (4-20 mA current loop), then device compatibility and simplicity are maintained, but predictive maintenance capability and real-time error detection are lost
Solution Approach 1:
The patent introduces an intermediary evaluation system that collects data from field devices via analog communication channels and performs stress analysis externally. This mediator enables predictive maintenance capabilities without requiring the field devices themselves to be complex or digitally advanced, thus maintaining compatibility while adding reliability.
Solution Approach 2:
The patent replaces the need for complex digital communication infrastructure with a mathematical evaluation model that processes basic analog signals. Instead of upgrading communication hardware, the solution uses computational methods (stress evaluation, load calculation) to extract predictive information from existing analog channels.
2Reliability
If field devices provide real-time error detection and status information, then maintenance can be predicted and planned, but device complexity and cost increase
Solution Approach 1:
The evaluation system performs self-service by autonomously collecting operational data, calculating stress levels, and generating maintenance recommendations without requiring complex modifications to the field devices. The system serves itself by using its own computational resources to analyze data from simple analog inputs.
Solution Approach 2:
The patent performs preliminary stress evaluation and load calculation to predict future failures before they occur. By analyzing accumulated stress data and operational patterns, the system proactively identifies potential issues, allowing maintenance to be scheduled in advance rather than reacting to actual failures.
3Ease of operation
If field devices are replaced only after failure occurs, then operational simplicity is maintained, but production downtime and costs increase
Solution Approach 1:
The patent establishes a feedback loop where operational data from field devices is continuously collected, analyzed for stress accumulation, and used to generate maintenance recommendations. This feedback mechanism enables proactive identification of deteriorating components, allowing planned replacements during scheduled maintenance windows rather than unexpected failures during production.
Solution Approach 2:
The system performs preliminary failure prediction by analyzing stress accumulation patterns and operational history. By identifying components approaching failure thresholds before actual failure occurs, the system enables advance scheduling of maintenance activities, preventing production downtime while maintaining simple operational procedures.
Data Source
Figure 1
AI summary
The invention relates to a method for monitoring a process automation system (A), wherein a plurality of field devices (FG1, FG2) and a plurality of additional system components (AK1, AK2) are integrated into the system (A), and the field devices (FG1, FG2) generate data, in particular measurement data, control data, calibration/parameterizing data, and diagnostic, history, and/or status data. The field devices (FG1, FG2) are connected together and to at least one higher-level unit (SPS) for communication purposes by means of a first communication network (KN). The method has the steps of: - continuously detecting production data (PD) from the system (A), said production data (PD) representing the quantity of produced products correlated over a defined interval of time; - calculating individual load data for each of the system components (AK1, AK2) and each of the field devices (FG1, FG2), said load data representing a degree of load for each of the system components (AK1, AK2) and each of the field devices (FG1, FG2) for each produced product; - continuously adding together the degree of load for each of the system components (AK1, AK2) and for each of the field devices (FG1, FG2) using the detected production data (PD) on the basis of the load data; and - generating a warning notification if the degree of load of a field device (FG1, FG2) or a system component (AK1, AK2) exceeds a threshold individually defined for each system component (AK1, AK2) and each field device (FG1, FG2).