AR Maintenance Guidance for Data Center Cost Estimation
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Solution Overview
Problem
Maintenance procedures in data centers are inefficient and lack effective guidance, leading to potential errors and increased costs due to the complexity and variety of devices and components.
Innovation Solution
An augmented reality headset is used to provide interactive maintenance guides, incorporating natural language processing and machine learning to adapt guidance based on user feedback, location, and performance, while evaluating and adjusting costs accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional maintenance procedures are used without augmented reality guidance, then device complexity and variety lead to inefficiency and errors, but implementing AR guidance increases system complexity and initial cost
Solution Approach 1:
The patent introduces an augmented reality headset as an intermediary device between the maintenance worker and the data center equipment. The headset displays guidance scripts, highlights components, and provides real-time instructions, acting as a mediator that simplifies the interaction between the worker and complex equipment without requiring the worker to directly navigate the complexity of maintenance procedures
Solution Approach 2:
The system implements feedback mechanisms where the AR headset tracks user eye movements, detects which components are being viewed, and adjusts the guidance script accordingly. The system also tracks maintenance performance data and uses it to refine future guidance, creating a closed-loop system that continuously improves based on user interaction and performance outcomes
2Measurement precision
If fixed base costs are used for maintenance procedures, then billing is simple, but cost accuracy deteriorates when actual activity varies from expected norms
Solution Approach 1:
The patent transitions from static, fixed base costs to dynamic cost evaluation. The system adjusts costs in real-time based on actual maintenance activity data, including time spent on tasks, complexity of procedures performed, and performance metrics. This dynamic approach ensures cost accuracy reflects actual resource consumption while the AR system automatically manages the complexity of calculations
Solution Approach 2:
The AR headset automatically tracks and records maintenance activity data without requiring manual time sheets or administrative intervention. The system self-monitors performance metrics, compares them against established benchmarks, and automatically adjusts cost evaluations, eliminating the need for complex manual cost tracking processes
3Reliability
If detailed tracking of user activity data is implemented, then cost accuracy and performance evaluation improve, but data processing requirements and system complexity increase
Solution Approach 1:
The system implements selective tracking of activity data, focusing on the most critical performance metrics and maintenance parameters. Rather than capturing every possible data point, the system tracks only the essential information needed for cost evaluation and performance assessment, reducing data processing requirements while maintaining evaluation reliability
Solution Approach 2:
The patent extracts and processes only the essential activity data needed for cost evaluation and performance tracking. The system filters out redundant information and focuses computational resources on analyzing critical maintenance metrics, thereby reducing overall data processing energy consumption while maintaining reliable performance evaluation
Data Source
AI summary
A method, computer program product and computer system to evaluate maintenance performance in a data center is provided. A processor provides an augmented reality device to a user performing a maintenance procedure, where the augmented reality device displays a guidance script to the user while performing the maintenance procedure. A processor determines an initial base cost associated with the maintenance procedure. A processor retrieves user activity data regarding the performance of the maintenance procedure. A processor determines an activity cost of the user performing the procedure. A processor, in response to the activity cost varying a threshold amount from the initial base cost, adjusts the initial base cost of the maintenance procedure based on the activity data of the user regarding the performance of the maintenance procedure.