Building Management Fault Prioritization UI for Remote Service Decisions
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Solution Overview
Problem
Determining whether to dispatch a service technician to a location or remotely service equipment experiencing faults is difficult, leading to inefficiencies and increased emissions.
Innovation Solution
An automated system using machine learning models to detect and rank equipment faults, generate observations and recommendations, and provide them via a user interface, optimizing fault prioritization and resource allocation for faster servicing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If service technicians are dispatched to equipment locations for fault diagnosis and repair, then comprehensive on-site servicing can be performed, but travel time increases emissions and reduces productivity
Solution Approach 1:
The system enables self-service through automated fault detection, diagnosis, and resolution mechanisms. AI models analyze equipment data to identify faults and generate repair recommendations without requiring immediate human intervention, allowing equipment to be serviced remotely or with minimal on-site presence
Solution Approach 2:
The patent introduces an AI-based intermediary system that acts as a mediator between equipment faults and human technicians. The system processes fault data, prioritizes issues, and guides technicians through automated workflows, reducing the need for physical dispatch while maintaining effective fault resolution
2Reliability
If multiple equipment faults are addressed without prioritization, then all equipment issues receive attention, but time and resources are wasted on non-critical faults
Solution Approach 1:
The system changes the parameter of fault prioritization by introducing multiple scoring dimensions (criticality, safety impact, operational impact, cost impact). This multi-parameter approach transforms fault assessment from a single metric to a comprehensive evaluation system that automatically ranks faults by importance
Solution Approach 2:
The patent implements preliminary action through pre-established fault prioritization criteria and automated scoring mechanisms. When faults are detected, the system immediately evaluates and ranks them against predefined parameters, preparing a prioritized action plan before technicians are deployed
3Measurement precision
If manual fault analysis and prioritization are performed without automated systems, then detailed human judgment can be applied, but the process becomes complex and time-consuming
Solution Approach 1:
The patent replaces manual fault analysis mechanisms with automated AI-based systems. Machine learning models process equipment data to detect faults and prioritize them, substituting human judgment with algorithmic analysis that maintains precision while reducing operational complexity
Solution Approach 2:
The system implements a universal AI platform that performs multiple functions: fault detection, diagnosis, prioritization, and recommendation generation. This multi-functional approach consolidates what would otherwise require separate manual processes into a single automated system
Data Source
AI summary
A system includes a plurality of equipment devices, and a controller including a memory storing instructions that, when executed by a processor, cause the processor to: obtain equipment operating data characterizing operation of a plurality of equipment devices, detect or predict a plurality of faults in the operation of the plurality of equipment devices based on the equipment operating data, analyze, using a machine learning model, the plurality of faults, rank, using the machine learning model, the plurality of faults according to one or more parameters of the equipment operating data, generate, using the machine learning model, one or more observations relating to the operation of the plurality of equipment devices and one or more recommendations to resolve the one or more faults, and generate, by the one or more processors, a user interface displaying the one or more observations and the one or more recommendations.