Asset Maintenance Analytics Switching to Prevent False Service Cases
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Solution Overview
Problem
Existing asset management systems fail to provide a holistic view of multiple analytic models, leading to unoptimized management and under-utilization of resources due to unobserved internal anomalies, erroneous service cases, and inefficient maintenance scheduling.
Innovation Solution
A system and method for managing service cases during asset maintenance that includes disabling and re-enabling analytic models based on maintenance schedules, providing a visualization of execution status, and generating recommendations for model applicability to improve asset performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple analytic models are continuously monitored for all assets, then detection precision of asset anomalies is improved, but device complexity and resource consumption increase
Solution Approach 1:
The system dynamically adjusts the monitoring state of analytic models based on asset maintenance schedules. During maintenance periods, analytic models are automatically disabled to reduce complexity; during normal operation, they are enabled to provide precise anomaly detection. This dynamic switching resolves the contradiction by adapting system complexity to operational needs.
Solution Approach 2:
The system performs preliminary actions by pre-scheduling maintenance activities and pre-disabling analytic models before maintenance begins. This prevents false anomalies during maintenance and reduces system complexity in advance, while ensuring precise monitoring is restored immediately after maintenance completion.
2Measurement precision
If analytic models are monitored during maintenance schedules, then measurement precision is improved, but erroneous service cases increase
Solution Approach 1:
The system applies preliminary anti-action by disabling analytic models before maintenance activities begin. This prevents the models from generating erroneous service cases during maintenance when asset behavior may be abnormal. The anti-action is reversed after maintenance completes, restoring precise monitoring without the harmful erroneous cases.
3Reliability
If comprehensive asset monitoring is maintained, then reliability is improved, but loss of time in maintenance operations increases
Solution Approach 1:
The system implements periodic action by alternating between monitoring phases (normal operation) and non-monitoring phases (maintenance). Analytic models are enabled during normal operation to ensure reliability, then disabled during maintenance periods to reduce time loss. This periodic switching optimizes both reliability and maintenance efficiency.
Data Source
AI summary
Various embodiments described herein relate to systems and methods for managing service cases during asset maintenance in a facility. In this regard, asset data is received corresponding to at least one asset of a plurality of assets. A plurality of analytic models is determined that are enabled corresponding to the at least one asset based on the received asset data. Further, it is determined that a maintenance is scheduled for the at least one asset. Based on the determination, at least one analytic model from the plurality of analytic models is disabled. Further, a holistic view of the plurality of analytic models corresponding to each of the plurality of assets is provided.