Fuzzy Index Early Warning for Industrial Equipment Operating Modes
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Solution Overview
Problem
Conventional systems for detecting equipment failures in industry plants rely on fixed threshold methods, which often result in delayed warnings due to binary evaluations, leading to potential production and quality losses.
Innovation Solution
A processor-implemented method that uses time-series data from sensors to compute concordance and discordance indices, derived from specific limits, to predict early warnings of equipment operating modes by transforming conditions into fuzzy indices, providing a composite degree of credibility for timely failure detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If fixed threshold methods with binary evaluation are used for failure detection, then the system is simple to implement, but the detection timing is delayed and early warnings are not provided
Solution Approach 1:
The patent transforms the binary threshold evaluation into a continuous fuzzy logic evaluation by introducing concordance index and discordance index parameters. Instead of simple yes/no threshold comparisons, the system calculates degree of credibility values that continuously indicate how close the system is to failure, enabling earlier detection warnings while maintaining computational feasibility through standardized fuzzy logic operations.
Solution Approach 2:
The patent adds a new dimension of evaluation by introducing the degree of credibility metric that ranges from 0 to 1, representing the likelihood of failure. This transforms the single-dimensional binary threshold check into a multi-dimensional assessment that includes concordance index, discordance index, and overall credibility score, enabling progressive warning levels before actual failure occurs.
2Measurement precision
If fixed threshold methods are used for failure detection, then the implementation is straightforward, but the detection precision is insufficient for early warning
Solution Approach 1:
The system replaces fixed threshold parameters with dynamic fuzzy logic parameters including concordance index and discordance index. These parameters allow for gradual transition from normal to failure states, providing precise early warning detection by measuring the degree of credibility rather than relying on abrupt threshold crossings.
Solution Approach 2:
The patent introduces fuzzy logic as an intermediary layer between raw sensor data and failure detection decisions. The concordance index and discordance index act as mediator parameters that process uncertain and gradual changes in process variables, enabling more precise detection of incipient failures before they cross traditional fixed thresholds.
3Productivity
If binary evaluation of detection conditions is used, then the system is easy to operate, but early warnings of failure onset are not provided leading to production losses
Solution Approach 1:
The system performs preliminary failure detection by calculating degree of credibility values that indicate the likelihood of failure before actual failure occurs. By monitoring concordance and discordance indices, the system provides advance warning signals that enable operators to take preventive actions, maintaining production continuity while using systematic fuzzy logic evaluation that remains operationally manageable.
Data Source
AI summary
Currently solutions for early detection of failures in manufacturing utilize predefined threshold levels of the process variables associated with equipment in manufacturing unit/industry plants. The pre-defined threshold and levels thereof are compared with the real values obtained from the manufacturing unit to check behavior of process variables (also referred as ‘process parameters’) and thus are prone to error. The present disclosure provides systems and method for predicting early warning of operating mode of equipment operating in industry plants which is based on transforming conditions on process parameters into conditions on corresponding fuzzy indices based on their thresholds. The fuzzy indices (concordance index, discordance index) of individual conditions are combined into a composite fuzzy index (composite index or degree of credibility) that describes the failure scenario in the process parameter space. A fuzzy logic-based detection is useful for detecting a failure mode early and providing alerts to operators for necessary action.