Readiness Assessment for Repairable Systems Using Probabilistic Maintenance Analysis
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Solution Overview
Problem
Conventional resource allocation techniques for electromechanical systems, such as aircraft, fail to accurately assess the relative readiness of systems post-maintenance, leading to inadequate selection for missions, as they only consider operability without accounting for the systems' relative status or degree of readiness.
Innovation Solution
An automated method and system that assesses the readiness of repairable systems by analyzing maintenance information using probabilistic processes like the modulated power law process, gamma renewal process, or homogenous Poisson process to determine the relative states of readiness, allowing for prioritization of maintenance resources and selection of systems most likely to successfully complete tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional resource allocation techniques are used to identify operational systems, then the systems can be selected for missions, but the relative degree of readiness cannot be determined
Solution Approach 1:
The patent introduces an intermediary assessment layer between maintenance operations and mission allocation. This intermediary system evaluates the relative degree of readiness of repairable systems by analyzing maintenance information and applying probabilistic models, thereby providing the missing readiness information without directly altering the maintenance or allocation processes themselves.
Solution Approach 2:
The patent replaces the conventional binary operational/non-operational assessment mechanism with a probabilistic readiness assessment system. Instead of using simple yes/no criteria based on minimum equipment lists, the system substitutes a sophisticated analytical approach using modulated power law processes and gamma renewal processes to calculate relative readiness degrees.
2Reliability
If maintenance operations are performed on repairable systems, then the systems can be returned to operation, but the relative status or degree of readiness cannot be accurately assessed
Solution Approach 1:
The patent transforms the readiness assessment from a discrete binary parameter (operational/non-operational) to a continuous probabilistic parameter (relative degree of readiness). By changing the assessment parameter from a simple operational status to a probabilistic measure based on maintenance information analysis, the system achieves precise measurement of system readiness states.
Solution Approach 2:
The patent introduces dynamic assessment of system readiness by considering the temporal aspects of maintenance operations and their impact on system status. The readiness assessment is not static but dynamically calculated based on the specific maintenance operations performed, the system's history, and probabilistic models that evolve with new information.
3Ease of operation
If systems are selected based only on minimum equipment list operability, then resource allocation is simple, but mission success probability is reduced
Solution Approach 1:
The patent applies partial action by implementing readiness assessment only for systems requiring mission allocation, rather than continuously assessing all systems. The assessment is triggered selectively when resource allocation decisions are needed, balancing the additional analytical effort with the specific need for informed decision-making at critical allocation points.
Data Source
AI summary
An automated method, system and computer program product for assessing the readiness of a plurality of repairable systems, such as a fleet of aircraft, are provided. In addition to identifying the repairable systems that will be operational, the relative state of readiness of the repairable systems is determined such that the repairable systems that are most likely to successfully complete the designated task can be selected. Additionally, an automated method of analyzing the maintenance operations performed upon a plurality of repairable systems, such as a fleet of aircraft, is provided. In this regard, the relative states of readiness of the repairable systems are determined and maintenance resources are allocated based upon the respective measures of the relative states of readiness of the repairable systems. As such, maintenance operations scheduled for the aircraft that will have the greatest state of readiness upon completion of the maintenance operations can be prioritized.