Technology

Tech firm develops machine learning for predictive maintenance

March 29, 2019
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Service Express OnDeck
Photo via youtube.com

A local tech company has launched a system to expedite the search for new parts.

Service Express recently debuted OnDeck, its latest proprietary parts sparing system. With OnDeck predictive sparing, Service Express identifies and stocks the parts needed for repairs, resulting in a faster reaction to data center outages and more operating time for its customers’ data centers.

OnDeck is able to identify all usage trends from over a decade of parts data. Updates run in real time, so changes in parts usage are identified immediately, according to the company. The system responds by making transfers, setting new reorder points, or adjusting local inventory so customers have the part they need before they actually need it.

“OnDeck predictive sparing allows us to be proactive about our support instead of reacting to every data center outage,” said Jake Blough, chief technology officer and creator of OnDeck. “Being able to predict future data center failure scenarios gives our customers confidence that we’ll have the right part available when they need it no matter what time or day that is.”

Blough said Service Express built the original version of the OnDeck program in 2007, and the company has been continually updating it as new technology and new data sets became available.

To ensure customer success, Service Express engineers complete a full equipment audit for every new data center, collecting the configuration information to connect to OnDeck. The system runs 24/7/365 for the most up-to-date view of parts usage by the server, storage and network equipment of the primary OEM brands, such as HPE, IBM, Dell EMC and more, he said.

Founded in 1993 and headquartered in Grand Rapids, Service Express maintains multivendor data center equipment for hospitals, manufacturing plants, universities, banks, Fortune 500 companies, financial institutions, government agencies and other mid-to-large companies worldwide.

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