Predictive Maintenance, the 1st Step Towards Self-Maintenance and AI

Many businesses are already using continuous monitoring technologies - like Internet of Things (IoT) connected devices - which is a good start; but the key lies in not just simply monitoring the output of various data (which is how many companies use it today), but by taking the next step and employing advanced algorithms and machine learning to take action from real-time insights and anticipate future outcomes.

Machine Learning for Asset Maintenance

Unsupervised Machine Learning is much more cost effective than Supervised Machine Learning because the algorithm does not need blueprints or understanding of the physical process to "learn" the behavior of the asset.

Robot Monitoring and Preventive Maintenance Solution

A robots abnormal condition can be detected early via data comparison, so a high-speed equipment monitoring solution must be able to acquire analog signals at the rate of 1000 signals per second. Then the collected signals need to be delivered to the control room for monitoring management and data analysis.

Maintenance Trends in 2017

Remember that these trends are already in place, for the most part. What you'll deal with are advancements and enhancements that make the trends more apparent.

One-Stop Repair for Food & Beverage Processing Equipment

Food and beverage processors speed repairs and reduce costs by working with single source for full gamut of machine repairs, from electronic controllers to motors.

Automatic Lubrication Systems That Stand Up to Corrosive, Caustic Environments

The latest in automated lubrication systems ensure optimum equipment performance, even in harsh plant environments, and reduce unscheduled maintenance. Corrosive plant environments are among the most serious threats to many industries today, contributing to extensive production downtime and exorbitant maintenance costs.

Factory Equipment Maintenance and Industry 4.0

The automation and collection of information thats available from machine to machine communication enables manufacturers to transition from corrective to preventive maintenance and ultimately to predictive technologies which rely on more information and data collection.

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