That AI is ubiquitous is a known fact. However, the uptake and adoption rates across industries isn't consistent. For software services, the progression to analytics and AI is a natural one, and this rapid adoption has set the ball rolling for other sectors to follow suit. Now, it's hard to find examples of industries not utilising AI for a range of benefits - maximising profits, enhancing quality inspections, monitor assets and the like. Specifically, enterprise asset management (managing an organisation's physical assets throughout their lifecycle) in India has been one of the late adopters of technologies like AI. It involves a fairly high capital investment, installation of hardware to track performance digitally, and manpower to monitor and analyse inputs. However, the tides are turning as these companies are open to working with technology providers and even startups to manage assets more efficiently. International Data Corporation data states that monitoring performance and scheduling repairs with predictive maintenance alone can reduce costs by 15%-20%, improve asset availability by 20% and extend the lives of machines by years. 

IndiGrid, India’s first listed power sector infrastructure investment trust, is keen on revolutionising modern enterprise asset management with digital technologies. IndiGrid owns 12 operating projects, consisting of 34 EHV overhead power transmission lines, comprising 7,765 kV transmission lines and 27,400 kV transmission lines across 15 states and 1 union territory in India. Satish Talmale, COO of IndiGrid, believes a "reliability-centred approach" to maintain demand-supply is the need of the hour. "Transmission is a highly labour-intensive sector and hasn't changed a lot in 70 years. Adoption and migration to digital technologies to manage assets requires an ecosystem to thrive and foster innovation. In the recent past, sectors like manufacturing have leapfrogged to digital, but the power sector largely continues to function under conventional practices. With a reliablity-centred approach, we aim to manage demand-supply proactively and stay ahead of asset maintenance-related hurdles," says Talmale. 

Conventionally, the power sector has largely relied on time- and condition-based approaches to maintain its assets but its becoming more obvious that these approaches aren't always effective. For instance, power transmission companies still rely on manual intervention to survey and inspect assets on ground. This can be particularly dangerous - each local transmission power line carries approximately 13,800 volts of electricity, which is then lowered and distributed for industrial and residential customers. Power lines are also situated outside residential areas, making access challenging especially during bad weather conditions. The risk of electrocution and other industrial accidents around such assets can be largely mitigated by harnessing digital technologies. IndiGrid has signed a multi-year collaboration agreement with IBM to build an Artificial Intelligence (AI)-enabled asset management platform. The IBM Maximo Application Suite will allow IndiGrid to monitor, manage and maintain multi-component assets efficiently and leverage AI for detecting anomalies at scale, proactively preventing breakdown. This will improve the overall health of power assets owned by IndiGrid and maximise the full potential of their operating life while adhering to safety and regulatory guidelines. Working with IBM Maximo will also help IndiGrid collect data to help build a digital transformation roadmap for the next five years. "Each tower generates about 50 data points, and IndiGrid owns about 10,500 towers - this is a lot of valuable data for us to understand the health of our assets and figure out what our next steps should be to enable improved predictive maintenance and performance," explains Talmale. 

While IBM is the first major collaboration with a technology solution provider for IndiGrid, the company collaborated with USA-based weather techology company ClimaCell last year. Ahead of Cyclone Amphan that made landfall mid-May and caused widespread damage in Eastern India, IndiGrid used ClimaCell’s predictive weather intelligence engine to avoid major disruption, damages, and ensure customers had power. Two days before the cyclone arrived, ClimaCell showed the customer across their 400 locations the expected time, duration, intensity, location, and impact of the storm giving them plenty of time to prepare. On the day of the cyclone, ClimaCell confirmed 10+ hours in advance the 2 locations that were at most risk of damage allowing the customer to focus and preposition crew members at those locations with a plan already in place. During the cyclone, the customer used ClimaCell’s HyperCast dashboard to stay in control and make decisions with confidence at the right times, including when the storm would be over so teams could immediately restore power. These measures helped IndiGrid prepare for the storm, focys on two at-risk locations out of 400+, gain visibility into any towers are at risk of high wind gusts, pre-position crews to ensure safety, understand the exact position of landfall to respond immediately, and document weather data for force majeure insurance. This intervention was particularly critical since India was in the middle of its first lockdown, and an extended power outage would be devastating, adds Talmale. Working with ClimaCell is especially a strategic advantage for IndiGrid, since its power lines extend across the country that experience a range of weather conditions like wind, snow and heavy rain, and can help the company prepare for unforeseen weather changes. 

Enthused by the results of these strategic collaborations, Talmale is keen on deploying other measures like drones for remote asset management and optimise existing optic cables to act as sensors for data gathering, instead of installing sensors. The bigger goal is however a four-phased strategy - asset management; asset performance using advanced analytics, AI, ML and Deep Learning; and asset lifecycle management by syncing up with OEMs for design risk - all of which will culminate into output investment planning with a high level of technology support and investment. "This is just the beginning of overhauling a conventional system, by utilising data, providing better working conditions for personnel, manage assets better and extend their longevity," he says.