How digital transformation kept workers safe during Covid-19
Digital transformation of heavy industry has never been more feasible, and necessary, than it is now. In fact, data shows that in response to Covid-19, corporate digital adoption has “vaulted five years forward” in just eight weeks as businesses have sought to digitalise significant areas of their operations. With health and safety front and centre, even field workers have been charged with finding new ways to carry out their work so that they can operate remotely too. In plants worldwide, the use of risk-based inspection and maintenance techniques has helped to reduce costs whilst keeping workers safe, and assets well maintained throughout this challenging time.
Digital transformation: a fundamental change
For many large industrial companies, digital transformation has been on the cards for a while, with most taking steps to implement digital strategies that bring long-term benefits to their operations. As a recent poll by Lloyd’s Register shows, nearly 40% of asset managers said that digitalisation is fundamental to their business, with a further 29% identifying it as important. This trend has only accelerated as companies have sought ways to retain a sense of business as usual in the face of the major disruption caused. Seeing the benefits of digital transformation first-hand, many businesses will begin to look at other ways they can benefit.
Contending with supply chain issues and the reduced availability of skilled resources, one function that has suffered from the disruption more than most is operations and maintenance. In our recent poll, only 14% of respondents reported no maintenance backlog, while 38% identified that it had been increasing. Without the ability to prioritise tasks effectively, an increasing backlog creates additional risk. Digital transformation can make all the difference by offering asset managers the ability to leverage a wealth of data to focus maintenance efforts.
Necessary tasks only
While several factors contribute to a rising backlog, one of the most significant is the number of maintenance and inspection tasks being scheduled that are unable to take into account extenuating circumstances, for example the constraints caused by a global pandemic. One of the major reasons for this is a reliance on time-based asset management techniques. Simply put, these techniques are not able to go far enough to identify and quantify the risk of failure, in comparison to the more advanced methods that are available. In practice this means that assets are often inspected or maintained without consideration for the actual condition of the asset or its risk profile.
Surprisingly, over 30% of all asset management teams continue to rely on time-based techniques, according to our research. During the height of Covid-19, this may have led to teams being called on site to inspect or maintain assets that were at low risk of failure. Further, as inspection and maintenance teams now return to work, those that rely on time-based techniques are likely to be met by a large backlog of work past its due date. Faced by a lack of insight into the assets that pose the highest risk, they will be unable to prioritise those jobs that need to be done first.
Meanwhile, teams that have transitioned to risk-based inspection (RBI) through a modern cloud-enabled system, have been able to manage much of their operations remotely all this time. When they have been required on site, it is to perform maintenance tasks that have been deemed as absolutely necessary for equipment categorised as having a high or medium-high risk of failure. Taking a risk-based approach to the inspection and maintenance regime has not only kept the plant safe but also lowered the risk of staff being exposed to Covid-19 in the workplace, by significantly reducing their time on site.
A risk-based approach doesn’t just deliver benefits in exceptional circumstances though. When companies initially implement RBI, they typically experience a decrease in the number of inspections required because the focus shifts to critical equipment. Since tasks are driven by the risk and particular condition of each asset, this results in intervals being extended and therefore plant shutdowns to become less frequent. Furthermore, RBI also reduces the risk of failure by 80% to 95% and the number of equipment items being opened by 30% to 60%. This equates to less time out in the field, and in danger’s way, 365 days a year.
A case in point, one company that has been ahead of the curve with its ability to work remotely and minimise risk to maintenance staff is a world-leading fertiliser company. They invested in an RBI solution from Lloyd’s Register as a means to improve safety and asset integrity.
On implementation it was identified that less than 5% of components were contributing to 95% of their cumulative risk. This enabled the operations and maintenance team to focus inspection on assets with high and medium-high probability of failure, avoiding safety consequences and production loss. Later, the company added asset performance management with LR’s AllAssets into their maintenance regime in order to provide a more accurate and up-to-date picture of the condition of their equipment and further enhance the strategy. All of this was possible because of their commitment to driving a step change in process safety, asset integrity and efficiency and the decision to digitally transform their operations and maintenance.
Returning to a business with less risk?
Businesses globally are executing plans to return to “business as usual”, and as we step out of the shadow of Covid-19, there has never been a better time to improve what business as usual looks like by committing to digital transformation. After all, no inspection and maintenance team should have to contend with months worth of backlog when a smart algorithm can optimise that plan in an instant while reducing the risk of failure and downtime too.
Oswaldo Rodriguez is a product manager at Lloyd's Register
Pure Storage: supporting the digital transformation journey
Pure Storage helps clients drive their competitive advantage by enabling data to deliver positive business outcomes such as evidence-based decision making using real-time analytics. “Working with the British Army, as part of an ecosystem of best in class solutions suppliers, Pure is providing private cloud services on-premise but also has offerings via AWS and Azure, and at container level,” explains Colin Atkinson Pure’s UK Public Sector Account Director.
“Pure Storage is supporting the digitalisation of the army as part of Programme THEIA,” reveals Colonel Mark Cornell, Assistant Head of Army Digital Services. “THEIA is how we change our ways of working to adopt more efficient digital processes. Technology is actually the easy piece of the puzzle; the challenge is cultural and behavioral change”. The army is a conservative organisation by nature, so how do we get its people - civilian, military, and contractors - to adopt the appropriate ways of working we want to deploy?
“We move away from labour intensive processes, and move further up the value chain to get the human adding value where they should be in the decision-making process.”
We’re in the midst of a data revolution highlights Atkinson. “We’re seeing an exponential growth in data analytics, which can create huge headaches for large organisations, or it can create massive opportunities. Data will be the oil that fuels this revolution….”
It’s a revolution that’s been gathering pace; each year, since 2016, 90% of the world’s data has been created in the previous two years. Atkinson also points out that 99.5% of historical data goes largely unanalyzed: “The corollary for large organisations is that if you don’t have a data strategy, you could end up with very large, very cold data silos and miss the opportunity to create that competitive advantage. By partnering with Pure we can help clients develop a data-enabling strategy.”.”
“We’re going to see a far greater use of data analytics in the British Army and across organisations in general,” forecasts Cornell. “We’re aiming for level three and level four predictive and prescriptive analytics approaches that start using Machine Learning and AI to give us deeper insights from our data. And as we move forward with Programme THEIA we see ourselves migrating our workloads and data into the cloud, making the use of the elasticity of hyperscale clouds. But also, protecting our data in the appropriate way if we wish to keep it on-prem and use it, and secure it in that way. We’re part of that cloud revolution that's going on through defense, but also across the wider public sector.”