Public Content Library

Using an Intelligent Predictive Maintenance Tool for Detecting & Predicting Equipment Failures at the University of Texas of Austin 

02-28-2019 15:52

Summary

UT-Austin took the next step in turning data into actionable intelligence by adopting HanPHI, HanAra’s predictive maintenance solution. UT-Austin recently expanded HanPHI from its CHP into its chilling stations and now receives early warnings of potential failures throughout the complex. By comparing real-time data to expected data created by HanPHI’s models, UT-Austin views the health status of its plant, systems, and equipment. UT-Austin benefits from reduced maintenance costs, unplanned downtime, and an increase in production.

Session 6A: Innovative Maintenance Strategies

Speakers

Sarah Kline, HanAra Software
Juan Ontiveros, University of Texas Austin 


#ConferenceProceeding
#2019
#CampusEnergyConference
#UniversityofTexasAustin
#Operations

Statistics
0 Favorited
7 Views
1 Files
0 Shares
2 Downloads
Attachment(s)
pdf file
6A.1_Kline_Ontiveros.pdf   2.55 MB   1 version
Uploaded - 02-28-2019