Sensor-Based Maintenance Prioritization System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
It is challenging for entities to proactively monitor and prioritize maintenance issues in physical locations, leading to potential equipment damage and customer impact due to the time-consuming nature of manual monitoring and inconsistent prioritization.
Innovation Solution
An automatic monitoring system utilizing sensors to measure properties of equipment and transmit alerts to a computing system, which identifies and prioritizes maintenance issues based on thresholds, ensuring timely attention to critical issues before they cause damage or impact customers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring of equipment is used, then employees can identify maintenance issues, but it is time-consuming and difficult to proactively monitor all equipment
Solution Approach 1:
The system enables equipment to self-report its status through integrated sensors that automatically detect and communicate maintenance needs without human intervention. Sensors monitor equipment conditions and trigger alerts when thresholds are exceeded, allowing the equipment to essentially monitor itself and request maintenance when needed.
Solution Approach 2:
The patent replaces manual mechanical monitoring with automated sensor-based detection systems. Instead of employees physically checking equipment, electronic sensors continuously monitor equipment status and automatically transmit data to the computing system, substituting human labor with automated electronic detection.
2Reliability
If employees manually prioritize maintenance issues, then they can address critical problems, but prioritization is inconsistent and may not prevent equipment damage
Solution Approach 1:
The system transforms subjective prioritization into objective parameter-based decision-making. The computing system evaluates multiple quantifiable parameters including equipment criticality, operational impact, and failure risk to automatically determine maintenance priority. This replaces inconsistent human judgment with consistent algorithmic evaluation of measurable parameters.
Solution Approach 2:
The system implements continuous feedback loops where sensor data is constantly monitored, analyzed, and used to adjust maintenance priorities in real-time. The computing system receives ongoing status updates from sensors and dynamically reprioritizes maintenance tasks based on changing equipment conditions and operational requirements.
3Reliability
If proactive monitoring is implemented to prevent equipment damage, then maintenance can be performed timely, but the system complexity increases with multiple sensors and computing requirements
Solution Approach 1:
The monitoring system is divided into modular sensor units, each responsible for detecting specific equipment parameters. Each sensor independently monitors its designated aspect and communicates with the central computing system, allowing the overall system to scale by adding or removing individual sensor modules without redesigning the entire system.
Solution Approach 2:
The computing system serves multiple functions: receiving sensor data, analyzing equipment status, determining maintenance needs, prioritizing tasks, and generating alerts. This multi-functional approach consolidates what could be separate complex systems into a single unified platform, reducing overall system complexity while maintaining comprehensive monitoring capabilities.
4Loss of information
If all maintenance alerts are transmitted to employees, then all issues are communicated, but unnecessary alerts waste employee attention and computational resources
Solution Approach 1:
The system applies selective alert transmission rather than notifying employees of all detected conditions. The computing system evaluates each maintenance issue against prioritization criteria and only generates alerts for issues that meet threshold levels of importance or risk. This partial action approach filters out low-priority conditions that would otherwise generate unnecessary alerts.
Solution Approach 2:
The system dynamically adjusts alert generation based on changing parameters such as equipment criticality levels, operational context, and historical failure data. By evaluating multiple parameters before triggering an alert, the system ensures that notifications are transmitted only when warranted by the actual state and importance of the equipment condition.
Data Source
AI summary
A system includes first and second sensors, and a computing system. The first sensor measures a first property of a first piece of equipment, and the second sensor measures a second property of a second piece of equipment. The computing system includes a processor and memory, which stores a condition that depends on both the first property and the second property. Satisfaction of the condition indicates that maintenance of the first piece of equipment should be prioritized over maintenance of the second piece of equipment. The processor receives the measured first property and the measured second property. In response to determining, based on the measured first and second properties, that the third condition is satisfied, transmits an alert for display on a user device. The alert indicates that maintenance of the first piece of equipment has a higher priority than maintenance of the second piece of equipment.