Building a Data-Driven Approach to Repair and Maintenance in the Energy Sector

by Sandeep Bhargava, Managing Director, APJ

Energy worker inside plant wearing a hard hat and typing on a laptop

Digital transformation is happening across the energy sector at a rapid pace. It is impacting almost every aspect of how companies do business, especially when it comes to repairing and maintaining their machines.

Internet of Things (IoT) is a buzzword in the industry. But an understanding of what it means and what challenges it can help the energy sector solve is often not clear. However, if we add in a descriptor such as “deploying smart devices that communicate over the internet,” the concept of IoT becomes much more meaningful.

Why connect devices over the internet? There are three main reasons — collecting data remotely, shortening feedback loops, and being proactive regarding maintenance risks.

  1. Remotely collecting data allows energy businesses to operate remote services more effectively to, for example, improve efficiency or safety.
  2. Connecting devices helps shorten feedback loops. For example, the data can deliver real-time insights into how customers use products or services. These insights provide a window of opportunity for fine-tuning them during the engineering and design stages.
  3. When companies are proactive in machine maintenance, they can spot potential risks before they become high-cost problems.


Generating Substantial Savings

Historically, businesses depend on taking a preventative approach to machine maintenance. However, downtime is too costly in an industry where the product (energy) is expected to be provided reliably and consistently. Avoiding downtime relies on replacing parts systematically rather than waiting for an actual problem to occur.

One of the ways the energy sector can benefit from a digital transformation and modernization is by utilizing intelligent, connected technologies that work behind the scenes, gathering and analyzing data 24 hours a day. These insights empower energy companies to generate substantial savings and provide better services.

According to The World Economic Forum, big data analytics is the second most likely technology to be adopted by businesses by 2025 — just behind cloud computing (see graph below). Big data analytics is being adopted rapidly because data-driven insights are invaluable to companies. In the case of IoT, big data is what the smart devices are communicating over the internet.

Implementing intelligent connected devices to collect and analyze data across your energy company’s supply chain will help you keep your costs down — and keep up with your competitors. 


Replacing Old-School Preventative Maintenance

While more cost-effective than downtime, the historical approach to preventative maintenance is still not budget friendly. For example, it often results in replacing functioning equipment before its end-of-life date, which is a considerable expense.

Today, instead of the old-school ways, you can use IoT-based, data-driven insights for preventative maintenance. This offers the ability to extend the lifetime of your machinery and significantly increase your cost savings.  

The secret is gaining access to new data streams related to machine maintenance and repair. For example, let’s say you are an energy company with wind turbines. Unfortunately, monitoring the health of your remote machine infrastructure efficiently typically results in high costs because you must rely on human interaction and guesswork.

But with remote access capabilities provided through IoT-based data collection and artificial intelligence (AI) analysis, you can observe what’s happening in real-time. You’ll know, for example, when the machines need attention based on insight into vibrations, sound levels, temperature, and more.

With this information, your engineering team can diagnose machinery performance from a distance and find problems before a failure occurs. This takes the goal of just-in-time maintenance to the next level versus the old-school way of prematurely fixing and replacing parts and machines. This modern approach lowers labor costs and saves the cost of unnecessary or too-early part replacements.

What’s more, since IoT-based systems are constantly collecting data, your processes get smarter over time. As you assess your machines’ data flow and execute repairs based on the data, the system will learn through AI to make even more accurate predictions.


Solving Together

Modernization, automation, and data management are transforming today’s energy sector. With a steady flow of data from your machines, you can achieve business outcomes based on strategic insights, which empowers your organization to save on labor costs and avoid expenses associated with premature machinery replacement.

Rackspace Technology® data modernization teams apply deep technical and business process expertise at scale to design and build data architectures — so you can accelerate innovation and realize value faster.

Take advantage of a complimentary strategy session to learn how Rackspace Technology can accelerate your path to becoming a truly data-driven business.

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