Predictive Analytics

In the bustling arena of the industrial landscape, the repercussions of unplanned downtime resonate deeply. According to a study by Aberdeen Research, unplanned downtime can cost a company as much as $260,000 an hour. Such challenges have been a persistent

Predictive maintenance has become a standard phrase in the equipment business and it is taking hold with OEMs. However, maintenance teams are not seeing much use for it. For them, “predictive maintenance is like chasing one’s own tail” – a

When it comes to production environments, it's always a question of how much can be produced, how quickly, and at what cost. At the end of the day, how efficient are we? Cycle time is one of the best measures we

Knowing how to manage and process data, information, is an asset of the digital enterprise. That's why analytics tools are becoming increasingly important in the manufacturing sector. As highlighted by Gartner in one of its Magic Quadrant for Analytics and Business

In countless applications that track live systems, real-time analytics play a key role in identifying problems and uncovering new opportunities. They enable data and operations managers to respond fast enough to make a difference in the moment. The need to

Today the Cloud represents the fruition model that makes Information Technology increasingly ready to respond to rapid changes in the context. Organizations are increasingly “data-driven”, and Data Analytics, a set of quantitative and qualitative approaches to obtain “valuable insights” from data,

What if your production equipment was always available as planned? What if your cycle time was never compromised because of a damaged machine? What if your production equipment self-detected and alerted you of quality defects? Applying Real-time Maintenance (RtM) technologies to your production

With the arrival of Industry 4.0 and the Industrial Internet of Things (IIoT), a digital transformation is currently underway. The manufacturing industry is beginning to use industrial analytics driven by real-time production data, not only to make better, faster decisions,

A large manufacturer with assembly and sub-assemblies mass produces automotive parts and components. A plant of this magnitude requires equipment, such as motors, pumps, compressors, fans, vibratory feeders, and other machines. The manufacturer had incurred significant financial losses, experiencing bottlenecks