Remote Maintenance Scoring for Medical Imaging Device Downtime
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Solution Overview
Problem
Conventional planned maintenance of medical imaging devices often results in unnecessary downtime and labor costs, as maintenance is performed at scheduled intervals regardless of the device's current state, potentially wasting resources on devices performing within standards and failing to address devices that have already degraded below acceptable performance levels.
Innovation Solution
A system utilizing a feature transformation algorithm to determine a degradation score based on sensor data from medical imaging devices, allowing for remote planned maintenance recommendations only when necessary, thereby optimizing maintenance tasks and reducing unnecessary interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If periodic planned maintenance is performed at scheduled intervals regardless of device state, then maintenance tasks are executed to ensure device reliability, but unnecessary maintenance tasks increase downtime and labor costs
Solution Approach 1:
The system performs preliminary monitoring and assessment of device condition through sensor data collection and degradation scoring before maintenance is actually needed. This allows maintenance to be scheduled based on actual device state rather than fixed intervals, preventing unnecessary downtime while ensuring reliability when truly needed.
Solution Approach 2:
The system continuously monitors device sensor data and provides feedback through degradation scores that indicate current device health status. This feedback loop enables dynamic adjustment of maintenance scheduling based on actual device condition, reducing unnecessary maintenance tasks while maintaining reliability standards.
2Reliability
If periodic planned maintenance is performed at scheduled intervals, then device performance standards are maintained, but labor costs increase due to unnecessary maintenance interventions
Solution Approach 1:
The system enables self-monitoring and self-assessment of device condition through automated sensor data collection and degradation scoring. This reduces the need for manual inspection during routine maintenance, allowing maintenance to be performed only when actually needed, thereby reducing labor costs while maintaining performance standards.
Solution Approach 2:
The system replaces manual assessment and decision-making with automated algorithms that analyze sensor data and generate degradation scores. This substitution of mechanical/human judgment with computational analysis reduces labor requirements while maintaining accurate assessment of whether maintenance is truly needed.
3Ease of operation
If traditional maintenance scheduling is used, then all devices receive equal attention, but resources are wasted on devices performing within standards
Solution Approach 1:
The system applies different maintenance priorities and resource allocation to different devices based on their individual degradation scores and actual condition. Instead of uniform treatment, each device receives maintenance attention proportional to its actual need, eliminating resource waste on devices performing within standards while ensuring adequate attention to degraded devices.
Solution Approach 2:
The system changes the scheduling parameter from fixed time intervals to condition-based degradation scores. This parameter transformation allows resources to be dynamically reallocated based on actual device state, reducing waste on healthy devices while directing resources to those needing maintenance.
Data Source
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AI summary
One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to a process to facilitate remote planned maintenance of medical imaging devices. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an input component that receives sensor data from at least one medical device, and a degradation component that utilizes a feature transformation algorithm to determine a degradation score for a planned maintenance task of the at least one medical device based on the sensor data. Additionally, the computer executable components can comprise a planned maintenance component that recommends maintenance for the at least one medical device based on the degradation score.