As industrial automation continues to digitize, one area in particular is becoming a critical area of concern– unplanned downtime. The shift to outcome-based business models, equipment assets becoming more sophisticated and connected, and of course, the pervasive and increasing reliance on machines, are all adding to the pressure to avoid outages. Mitigating downtime is now a strategic priority in the digital age.
Take power as an example. In the US, generating units are unavailable on average for 15% of the time due to outages and maintenance. In fact, 6% of the time they are unable to meet demand at all. And the Energy Information Administration highlights that a further 6% of electricity is lost in transmission and distribution due to both technical factors and outages.
The growing reliance on automation is already widening performance gaps. Businesses are losing sight of assets, especially in terms of efficiency, leading to a fractured insight of manufacturing or service delivery. The upshot is that unplanned downtime becomes a real problem and even worse, the lack of visibility leads to an unnecessary lengthening of recovery time. Closing this downtime gap is a fundamental step in an organization’s digital maturity, and a core part of their transformation journey.
According to a recent Vanson Bourne global study After The Fall: Cost, Causes and Consequences of Unplanned Downtime, 82% companies have experienced at least one unplanned downtime outage over the past three years, and two on average. These outages have lasted four hours. Depending on the company and type of equipment, this can cost organizations anywhere from $50k-$150k per hour for say, a medical device company, and up to $2m for a major outage on an industrial critical asset. (Aberdeen estimates the cost across all businesses to be $260,000 an hour). The research also revealed high levels of asset estate ignorance across organizations, with 70% of companies lacking full awareness of when equipment is due for maintenance, upgrade or replacement.
In addition to financial losses, the research found that almost a third of respondents said they were unable to service or support specific equipment assets, while 65% of respondents from the energy and utilities sector, and 62% from the medical sector cited losing the trust of their customers as a possible impact of suffering a high-profile incident or disaster. Across all sectors, around one in ten admitted their company would never recover from such critical incidents and would ultimately cease to exist. Nobody wants to be blindsided with those sorts of numbers. But what are companies doing about it?
The research hints at a tipping point in recognition of the problem and planned investment to address it. Over time, zero tolerance and zero unplanned downtime will become the norm as companies develop and invest in their industrial digital strategies. Key to this, is an understanding of and investment in field service management and asset performance management capabilities.
According to Vanson Bourne, eight in ten companies have already recognized this, at least that digital tools can improve visibility of assets and help eliminate unplanned downtime. Around 50% of companies confirmed they plan to invest in field service and asset management technologies in the next three years, while 72% of firms claim that zero unplanned downtime is now a number one priority. So, the message is sinking in at least.
The challenge for most businesses is to digitally transform without losing oversight of key products, services and of course assets. Digital transformations do not automatically improve control and visibility. Companies need to pursue a service-led approach to business, to ensure that their ability to manage the actual assets that make products or ensure services run smoothly are always up and running. A clear asset management and predictive maintenance strategy should ensure that businesses take the right path towards reducing, if not completely eliminating downtime.
Understanding problems before they happen and having knowledgeable and digitally-empowered service technicians to ensure the smooth running of assets will go a long way to making this happen. A digital twin of physical assets will help considerably here, and the research has revealed that around 54% of companies are planning to invest in a digital twin by 2020. Throw-in the fact that field service is expected to become a primary revenue driver for most businesses within the next two years and you have a recipe for transformation.
We often hear the phrase, ‘you cannot account for human error’ but that seems illogical in today’s connected world. We have the technology to not just account for human error but to eradicate it. The internet of things with the proliferation of affordable and reliable sensors is changing the way in which we can view, manage, service and support technology, processes and any physical object. By mirroring a process, product or service into a virtual world, we can create environments in which machines can automatically analyze performance, warn of impending issues, identify existing or potential errors and even suggest part upgrades or changes to procedures to make them more efficient.
This is the digital twin idea. As a concept, it’s been around for a while (NASA used it on early space missions) but the emergence of IoT has made it a commercial reality. Digital twin eliminates guesswork from determining the best course of action to service critical physical assets, from engines to power turbines. Easy access to this combination of deep knowledge and intelligence about your assets paves the road to wider optimization and business transformation.
Digital twin technology spans across all industries where the value is in assets and more generally complex systems. Its ability to deliver early warnings, predictions, and optimization is fairly universal. In time, I think we’ll see the concept of a digital twin to be applied to human beings as well, playing a significant role in healthcare.
However, just mirroring is not enough. If the aim is to achieve zero downtime or at the very least, overall insight into on-going product and process performance, the digital twin has to be analyzed and that analysis has to feed other functions. What the digital twin produces, when bundling data with intelligence, is a view of each asset’s history and its potential future performance.
The digital twin can use historical data and current data to provide a complete picture of a particular asset, its past performance, what it should be achieving now and its likely end of life date, when it would be predicted to be less efficient. This sort of knowledge is gold dust for product designers and manufacturers as it can feed back accurately, which parts work well and where machines would need improving or upgrading.
Combined with the knowledge of field service professionals this makes for a powerful tool for upselling products and services to customers. Any new ideas or enhancements can be fully supported with data analysis and perhaps even simulations to illustrate how new parts and functions would improve performance. It offers justification and also accountability and should cut through irrelevant or unsuitable product or service ideas. It’s transforming service at the edge by bringing together all the facets that make businesses and machines tick - and goes a long way to creating a world of zero unplanned downtime.