Field Device Maintenance via Error Image Pattern Matching
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Solution Overview
Problem
Field devices in industrial automation systems often require time-consuming and costly maintenance due to malfunctions, as operators struggle to quickly identify and address issues based on diagnostic messages, leading to potential system downtime and increased expenses.
Innovation Solution
A method and system that record and analyze diagnostic messages from field devices, correlate them with past error patterns, and provide experience-based suggestions for corrective measures, including predictive maintenance, to facilitate quick and efficient problem-solving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If maintenance experts manually evaluate and analyze diagnostic messages based on individual experience, then problem-solving accuracy can be achieved, but time consumption and expenses increase significantly
Solution Approach 1:
The patent creates error images that are copies or representations of actual error situations encountered in the field. These error images capture the essential characteristics of diagnostic messages and their corresponding successful resolutions. When a new diagnostic message occurs, the system compares it against the stored error images to identify matching patterns, thereby copying proven solutions from past experiences without requiring manual expert analysis each time.
Solution Approach 2:
The system performs preliminary actions by pre-processing and storing diagnostic messages along with their successful resolutions in the form of error images before they are needed. This advance preparation allows the system to quickly retrieve and compare against known error patterns when problems occur, eliminating the need for time-consuming manual evaluation and enabling rapid identification of appropriate corrective measures.
2Reliability
If field devices are maintained proactively with predictive capabilities, then system reliability improves, but system complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where diagnostic messages from field devices are continuously collected, analyzed, and stored as error images. The system then uses this feedback loop to compare new diagnostic messages against the accumulated knowledge base, automatically generating suggestions for corrective measures. This feedback-driven approach enables proactive maintenance by learning from past errors and applying that knowledge to prevent or quickly resolve future issues.
Solution Approach 2:
The system enables self-service maintenance capabilities by automatically comparing new diagnostic messages against the stored error images and generating suggestions for corrective measures without requiring immediate human intervention. The plant operator can use these automated suggestions to quickly resolve issues, reducing the need for specialized maintenance expertise and enabling faster response times while maintaining system reliability.
Data Source
Figure 1
AI summary
The invention relates to a method and a system for maintaining at least one field device in a plant using automation technology, comprising: • - a plurality of field devices; • - a database for storing the device types of the field devices, diagnostic messages regarding the field devices, error images, measures taken in the past to repair errors/faults, and assessments of the success of the stored measures; • - a computing unit that accesses the database and can read, store and/or associate data in the database, makes assessments of the success, compares new diagnostic messages with the error images stored in the database, and displays a suggested suitable measure and the assessment of the success thereof.