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Advancing from Data Visualization to Data Interpretation with Meaningful Insights

The role of data in our everyday lives has never been more prevalent. As we walk around with smartphones and fitness monitors that can track and report on nearly every movement we make, we have become more accustomed to this process of gathering and reporting data in our personal lives. However, this adoption is still facing some challenges in our professional lives.

A 2019 study found that although data gathering tools are more accessible than ever, professionals are still struggling to effectively incorporate them into their workplace. Among respondents, 50% say they “lack the tools to feed downstream apps with the right data at the right time,” and 44% “simply lack the time to sort through data.” Perhaps, most significantly, 53% say their team “lacks the IT skills or staff to work on extracting meaningful insights from data.”

As larger mining companies look to implement or advance their digital transformation strategies, these challenges of how best to interpret and act on the data collected become very real roadblocks. The most effective digital tools will address these concerns while helping organizations better plan maintenance, improve employee efficiency and safety and ultimately increase productivity.

Flexco Elevate™ is the first-of-its-kind belt cleaner monitoring technology designed to meet all of these needs and more. Flexco Elevate™ will not only seamlessly fit into a mining operation’s digital transformation strategy – it will help organizations rethink what is possible from their strategy.

At the heart of Flexco Elevate is the state-of-the-art Flexco Elevate™ i3 Device attached to every Flexco cleaner throughout the operation. The device was named in recognition of the key role that it plays: it collects real-time data and information, establishes patterns and builds models through intelligence and delivers insights that can be intuitively interpreted and acted upon by users and field operators.

To understand how Flexco Elevate helps mining operations run more efficiently by delivering actionable insights from the data it collects, it’s important to better understand the evolution of this self-learning technology once it is deployed in an operation:

Pulling Together Data

While data visualization is a component of Flexco Elevate, it is only the beginning. At its core, data visualization provides an intuitive and consolidated view of multiple data points throughout an operation in one convenient location. These are typically collected from multiple sensors or devices and can help offer a comprehensive view of an operation’s overall performance.

The continuous and automated collection and monitoring of data limits the need for on-site inspections – including those that could compromise employee safety – freeing up working hours and reducing costs. In many cases, these platforms also improve upon what is not possible from on-site inspections alone by “seeing the unseen.” The Elevate i3 Device, for example, relies on sensors that detect anomalies throughout a belt conveyor that couldn’t be easily detected by physical or visual inspection, delivering “the right data at the right time.”

Picking up Patterns

As more and more data is collected, the Elevate system will begin to pick up on patterns that reflect the day-to-day activity at an operation, helping users “sort through the data” more effectively. This helps create a history of typical or normal operation, thus establishing a baseline to easily identify and visualize outliers that signify abnormal events.

In the beginning, these abnormalities will be identified solely from a diagnostic perspective. In simplest terms, they alert the user that something doesn’t look to be functioning as the established patterns dictate. From here, it is the role of the user to determine if an event should be disregarded, acknowledged or further investigated. Over time, as the platform collects more data from the sensors and the data is acknowledged and validated, the data models grow smarter and more accurate in their assessment and reporting of operational insights and performance.

Predicting Future Performance

The final phase is marked by a transition from reporting to predicting, and this is what separates Flexco Elevate from traditional data visualization tools. Through edge analytics and machine learning, the Elevate system is able to interpret performance patterns and abnormal occurrences on its own and make predictions about future maintenance needs. For a heavy-duty conveyor belt operation, this might mean an inspection is needed or that a conveyor belt cleaner is due for maintenance and/or replacement.

The platform is now able to deliver real-time and predictive insights about the operation. This empowers the user to better understand the performance of the belt, predict future needs and maintenance, and potentially prevent a catastrophic event, resulting in a more efficient operation and reduced downtime. This ability to draw meaningful, actionable insights from data is what most companies perceive as the greatest challenge to utilizing data in the workplace, and it is the differentiator that sets Elevate apart from anything else in the field.

With a seemingly endless supply of data at our fingertips, the operations that will benefit the most from this technology are the ones that can most accurately and intuitively interpret the data and draw insights from it. Flexco Elevate was designed with this in mind, and delivers insights that produce ROI from day one by predicting maintenance needs, limiting the need for manual inspections, and improving overall operational efficiency.

Learn more about Flexco Elevate here or contact your local Flexco sales representative.

Authored by Shawn Akkila, IOT Solutions Architect

Shawn Akkila is a seasoned IT professional with over 28 years of experience working as an IT Consultant, Solutions Architect, and IoT Innovator.

Published Date

July 16, 2020

Product Group

  • Belt Cleaner Monitoring

Issues

  • Belt Protection
  • Belt Wear
  • Downtime
  • Maintenance

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