Deep Learning for Hard Drives Predictive Maintenance

May 18, 2020Blog, Solutions

Deep Learning for Hard Drives Predictive Maintenance

May 18, 2020Blog, Solutions

The power of Machine Learning for Predictive Maintenance

 

Predictive maintenance for industry 4.0 helps determine the condition of in-service equipment in order to estimate when maintenance should be performed. Its main goal is to prevent asset failure by analyzing production data to spot patterns and predict issues before they happen. Until now, factory managers and machine operators carried out preventive maintenance, scheduling it at regular intervals, but this is an ineffective activity that consumes unnecessary resources and drives productivity losses.

Thus, it’s not a surprise that predictive maintenance is quickly emerging as a number one Industry 4.0 use case for manufacturers and asset managers. Implementing industrial IoT technologies to watch asset health, optimize maintenance schedules, and gaining real-time alerts to operational risks, allows manufacturers to lower service costs, maximize uptime, and improve production throughput.

Our high-value use case shows how to quickly and successfully implement Predictive Maintenance within your organization

 

Read our Use Case to learn more

Online Machine Learning: INTO THE DEEP

Online Machine Learning: INTO THE DEEP

Online Learning is a branch of Machine Learning that has obtained a significant interest in recent years thanks to its peculiarities that perfectly fit numerous kinds of tasks in today's world. Let’s dive deeper into this topic. What exactly is online learning? In...

Alexa, make my database smart!

Alexa, make my database smart!

 Human and machine communication towards conversational analytics In recent years, smart speakers like Amazon Alexa, Google Home, and Apple HomePod have increased their market share, and according to the forecast, their popularity will continue to grow. Lots of people...

This is time for Time-series Databases

This is time for Time-series Databases

The history of Database management systems could be interpreted as a Darwinian evolution process. The dominance of relational databases gives way to the data warehouses one, which better adapt to the earliest business intelligence requirements; then, alongside the...