Why data-driven maintenance is the future for India's energy sector

With the transformation sweeping today's energy sector, a steady flow of data across devices and machines can provide the impetus

New Update
energy sector

With continued digitisation, India — like the rest of Asia Pacific — is at an energy crossroads. With the International Energy Agency having revised and downgraded its projection for India’s energy demand growth until the next decade, there is a very real risk of stunted social development for large swathes of the population. For India, S&P Global warns of an escalating energy crisis after the country posted a 14 percent on-year decline in spot LNG imports.


Furthermore, an Asian Development Bank policy paper identifies that despite digitisation, effective operation and maintenance of infrastructure is a key challenge for growing energy needs. For suppliers in India — the world's third-largest energy consumer — the question, then, is how can data and technological advancement be harnessed to continue empowering communities across India?

Despite its impact on improving infrastructure, the Internet of Things (IoT) is often unfairly dismissed as an industry buzzword. 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.

 Generate Savings Through a Proactive Approach

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 scaffold digital transformation and modernisation is by utilising intelligent, connected technologies that work behind the scenes, gathering and analysing 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 analyse 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 labour 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. With the transformation sweeping today's energy sector, a steady flow of data across devices and machines can provide the impetus for India's continued economic vitality. With greater clarity to decision makers, organisations can harness a host of savings — from reducing labour costs to avoiding premature machinery replacement — the region can better address its most pressing energy challenges and realise the enormous potential for a secure and smarter energy future. 

The article has been written by Sandeep Bhargava, Managing Director, Asia Pacific and Japan, Rackspace Technology