Predictive Maintenance with Incomplete Construction Data at Quantum Rise
From Constructed Futures, A Quantum Rise Podcast by Hugh Seaton
February 12, 2026 · 16 min · Episode 263
About this episode
The episode discusses how Quantum Rise addresses the incomplete data problem in construction through predictive maintenance and diagnostics.
We hear about construction's incomplete data problem, and too often the first response is to spend money and time cleaning it up before anything useful can be done. The data science capabilities of Quantum Rise give customers the ability to see value quickly with the data they have, while putting in place the systems to improve data going forward. A key use case is predictive maintenance and diagnostics, where heavy machines like excavators, milling machines and trucks can reduce downtime and service expense by understanding likely issues before they come up - all with data companies have now. Director of implementation Connor Schmeling walks through some client engagements where Quantum Rise has been able to provide highly useful tools, and set contractors up for future success with enhanced data collection.
People in this episode
Host: Hugh Seaton
Guest: Connor Schmeling
Topics covered
- predictive maintenance
- data science
- construction data
- diagnostics
- heavy machinery
- data collection
Keywords
- predictive maintenance
- construction data
- data science
- Quantum Rise
- heavy machinery
- excavators
- milling machines
- trucks
- data collection
Mentioned in this episode
Organizations: Quantum Rise
Products: excavators, milling machines, trucks
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