Smart Equipment Maintenance: Remote, Preventive and Cost-effective - Christopher John Hendy | HCL Blogs

Smart Equipment Maintenance: Remote, Preventive and Cost-effective

Smart Equipment Maintenance: Remote, Preventive and Cost-effective
June 11, 2020

Organizations in the mining, oil and gas, and natural resources sector are under constant pressure to maintain production uptime. The reason, of course, is the incessant demand and stiff competition. Over the 2018-2019 period, Australia broke records when it exceeded the billion-barrel mark in production. The milestone was a clear demonstration of how companies in this sector push the envelope to increase output.

But as market volatility shakes the global landscape, particularly in the wake of the COVID-19 pandemic, the path ahead seems uncertain. The matter is further complicated by the fact that the assets operated by the industry come at a very steep cost, ranging from a couple of million dollars to upward of $50 billion, if you include one-time fixed assets such as pipelines spanning hundreds of miles.

Clearly, investments run deep, and organizations are heavily interdependent on global supply chains and government regulations to keep things running smoothly. But even as demand fluctuates, it is critical for organizations in the industry to maintain their assets. They need to be prepared for sudden surges in demand. So, facilities, processing plants, equipment of all types, and fixed, large assets need to be fastidiously maintained and continuous production needs to be ensured.

Equipment maintenance, unfortunately, tends to be a reactive process. When production is aggressive and a breakdown occurs, the maintenance team scramble to try to fix the damage immediately. But for organizations to be future-ready, this approach needs to change.

Roadblocks to Reactive Equipment Maintenance

Aggressive production is not the only factor behind the reactive approach to systems upkeep. The lack of visibility into vital factors such as the production and installation of machinery, the availability of parts for replacement, and the repair chain, are all part of the problem. I recall the case of an Australian mining major that needed the engine of a caterpillar truck repaired. Once the engine was picked up by the repair agency, there was no visibility into the repair life cycle. The mining major was completely in the dark. When the company received the engine back from the agency, it was not the same unit nor was there any documentation of its repair history, how long it had been used, whether it had any special components. There were no details at all.

Another hurdle is the location of oil and gas operations sites. They tend to be in remote, far-flung corners of the world. This makes access to the machinery difficult and time-consuming. Unfortunately, it is not possible to permanently station repair mechanics or engineers on the sites either, as rigs have limited accommodation capacity, while the network of pipelines and substations are typically meant to host only operating staff. Moreover, the dearth of professionals with the required skillsets exacerbates the problem and its associated costs.

As a result of these challenges, oil and gas companies run their equipment on the OEM-recommended settings. They need to do this for the duration of their warranty period to stay covered. But once the warranty period has expired, companies often choose to continue with the same settings, despite the fact that it prevents the optimal functioning of the system. Doing so benefits OEMs far more than it helps the actual operators of such equipment. In addition, many companies have a fixed, rigid maintenance strategy that stays in effect throughout the lifecycle of the asset, irrespective of the changes in the frequency of use, commercial considerations, and the age of the asset.

Legacy maintenance strategies and protocols are some of the primary reasons why companies in the mining, and oil and gas sectors opt to buy new equipment, despite the astronomical prices, or defer maintenance activities until there’s a crisis. But even new equipment needs to be ordered, delivered, and installed, which takes time. Deferring maintenance or relying on replacing the old with the new may offer short-term gains, but this makes the value chain more susceptible to disruptions.

But change is afoot.

As industry players look at building reliance and future-readiness, digitization is on the rise. Companies are steadily moving toward leveraging smart systems and self-reliant machines where applicable. The industry is witness to a growing reliance on automated machines. An overhaul of the maintenance strategy is, therefore, imperative to ensure optimum equipment performance and uninterrupted operations.

From Reactive to Pre-emptive Maintenance

Organizations looking at rethinking their maintenance strategy are leveraging technologies such as robotic process automation (RPA), industrial internet of things (IIoT), edge computing, machine learning (ML), predictive analytics, and digital twins. These technologies have reached a maturity level where they can be confidently deployed at an industrial scale in the oil and gas landscape.

As RPA reduces the dependence on, or requirement of, manual effort for specific operations, human resources can be freed up to perform equipment maintenance tasks that require critical thinking or non-standard problem-solving. Integrating all systems in an IIoT allows machines to communicate securely within the safety of a private network. This gives oil and gas companies the data they need to have complete visibility—data that they currently lack. The data that emerges from a connected, communicating ecosystem serves multiple purposes. Apart from providing visibility and control, it serves as the fuel for predictive analytics, which, in turn, helps businesses pre-empt potential system vulnerabilities and resolve them before they escalate. As a result, machines have a lower chance of breakdown and can continue operating optimally with minimum losses due to downtime.

ML gives machines the ability to learn in real-time, as they operate. Coupled with edge computing, the systems can make sense of the incoming data, process it, and take the prescribed preventive actions, in real-time, without any human intervention. The strategic deployment of these technologies thus ensures remote monitoring and predictive maintenance. Timely repair and upkeep increase the equipment’s lifespan and save businesses millions of dollars that would otherwise have been spent on buying brand new components to replace malfunctioning ones.

Digital twins have a completely different role. A digital twin is an essential virtual replica or blueprint of an asset. A digital twin of an asset in the field gives companies a 360-degree view of even the remotest components in their value chain. A digital twin serves as a reference to verify and validate whether an asset, say a specific machine or an entire rig, is designed and constructed as per the specification. Maintenance, thus, becomes easy and predictable, with assured outcomes.

Survival of the Smartest

First movers in the mining, oil and gas industries have already woken up to the benefits of new technologies for proactive, cost-effective, and long-sighted equipment maintenance. Others would be wise to catch up quickly. 'Survival of the smartest' is the rule of the game in today's increasingly competitive global market. Pre-emptive asset maintenance that leverages next-generation digital technologies is the key for oil and gas companies to ensure seamless operations, maximum productivity, and adequate protection from future disruptions.

First movers in the mining and oil and gas industry have already woken up to the benefits of new technologies for proactive, cost-effective and long-sighted equipment maintenance.