Predictive Maintenance Software
The guy who invented the wheel probably learned very early that protecting his wheel from damage was much smarter than having to make a new one every time it broke.
Since then machines have gotten increasingly more complicated, and the cost of failure has become increasingly higher.
In the 20th century, preventive maintenance was the usual approach to reducing the risk of failure cost. Cars, airplanes, and other machines have scheduled maintenance intervals, design to prevent unexpected downtime. Taking your car in for service every 7,500 miles is preventive maintenance, and has been the standard model for keeping machinery running. But failure still happens, and it usually isn’t very polite about adhering to predetermined maintenance schedules.
Technology today allows predictive maintenance – machines that are actually smart enough to tell you when they need service, and accurately predict failure before it happens. Predictive maintenance software built into smart machines can dramatically reduce maintenance costs and improve throughput.
Even better, machine learning can be used to make the predictive analytics more accurate, further reducing downtime.
All of this is part of a larger trend called Industry 4.0 – a concept made possible by bringing together 21st century technologies such as cloud computing, big data, predictive analytics, and IoT (Internet of Things).
Tivix has developed custom predictive analytics software for a variety of sectors, from financial services to medical devices. But using predictive analytics for preventative maintenance is one of the most compelling use cases, with the capacity for delivering hard-dollar ROI.
Predictive Maintenance even crosses over into animal health. Tivix has developed software for our client Zoetis that helps livestock farmers know that their herd might be getting sick it’s much less expensive to cure a herd before they get sick.
So Ben Franklin was right when he said “An ounce of prevention is worth a pound of cure” (even though he probably didn’t know anything about predictive maintenance software).
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