Machine Heartbeat Monitoring for Process Variation Detection
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Solution Overview
Problem
Existing predictive methods for monitoring machinery and automated processes fail to sufficiently discriminate sources of variation, leading to inadequate prediction of conditions requiring intervention to prevent downtime, productivity loss, or quality issues.
Innovation Solution
A system and method for generating a 'heartbeat' of a process by ordering event durations of timed events, allowing for the comparison of current and prior heartbeats to identify trends and variations, and enabling predictive or preventive interventions through causal analysis and parameter monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If known predictive methods such as machinery vibration analysis are used to monitor machinery, then general process monitoring is achieved, but the ability to sufficiently discriminate sources of variation to effectively predict process conditions is insufficient
Solution Approach 1:
The patent segments the process monitoring into multiple discrete timed events within a process cycle, measuring the duration of each individual event (E1, E2, E3, etc.) rather than using general vibration analysis. This segmentation allows for precise identification of which specific event duration is varying, thereby discriminating the source of variation and enabling more reliable prediction of process conditions requiring intervention.
2Loss of information
If event durations of timed events are measured and ordered to generate a heartbeat, then detailed understanding of process variations is achieved, but the complexity of the monitoring system increases
Solution Approach 1:
The patent creates a simplified copy or representation of the complex process cycle by generating a 'heartbeat' sequence that captures the essential timing characteristics of multiple timed events. Instead of analyzing all raw process data, the system creates this condensed heartbeat copy that retains the critical timing information needed to understand process variations while being much simpler to store, transmit, and analyze.
3Reliability
If variance analysis between heartbeats is performed to monitor process conditions, then predictive maintenance capability is improved, but the computational requirements and processing time increase
Solution Approach 1:
The patent applies partial action by focusing variance analysis only on the critical timed events whose duration variations are most indicative of process conditions requiring intervention. Rather than performing exhaustive analysis on all process parameters, the system identifies and monitors only the key timed events that provide the necessary predictive information, thereby reducing computational requirements and processing time while maintaining effective predictive maintenance capability.
Data Source
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AI summary
A method and system for generating a heartbeat of a process including at least one machine configured to perform a process cycle consisting of timed events performed in a process sequence includes determining the duration of each timed event during performance of the process cycle, ordering the durations of the timed events in the process sequence, and generating a heartbeat defined by the ordered durations of a process cycle. One or more process parameters can be sensed and displayed with the heartbeat in real time. The variance of a current heartbeat to a baseline heartbeat and/or a comparison of a process parameter to a parameter limit can be analyzed to monitor and/or control the process or machine. The heartbeat, the process parameter corresponding to the heartbeat can be displayed on a user interface which can include a message corresponding to the heartbeat and/or the process parameter.