Change is not really a constant; it is a law. The next major change maker is the industrial internet of things (IIoT). Terms such as artificial intelligence, (AI), machine learning (ML) and digitalization fill headlines and are the topics of many articles, blogs, and whitepapers.
IIoT focuses on improving the connectivity of data/information from manufacturing/processing sources throughout the entire value chain of the products/processes. It involves the successful combination of instrumentation, sensors, software, hardware, and analytics of data. The ultimate goal is the linking, converting, and mining of critical data into usable knowledge that supports better decision making.
A step back or sideways
Energy and processing/manufacturing industries have been amassing huge volumes of data for many years. In truth, wireless and smart-device technologies ushered in the capability to add advanced sensors and instruments almost everywhere within an industrial unit. The data have been collected and stored in numerous places and databases. The lack of connectivity between the data and possible users created silos of information, which were difficult to access and use in meaningful ways.
Knowledge is power
For energy and processing companies, the issue has never been finding data. Rather, the true problem was identifying ways to sort through the tsunami of collected data in a time-efficient manner. For years, engineers have struggle to extract critical data from historians and databases, refine useful knowledge, and finally develop corrective actions. The motivating force of digitalization is to centralize access so that engineers and scientist can cull out essential data for analysis and graphical presentation of results for decision makers.
Digitalization is transforming business models and, more importantly, how data is collected, managed, and shared. More than IT and operational technology (OT), digitalization facilitates and integrates data from the field to end users. The International Energy Agency breaks digitalization into three areas:1
- Collection (digital) of data or information
- Analytics and visualization of selected data to develop information for more insightful decision-making or corrective plans
- Connectivity to easily share information with end users (human, machine, or devices.)
Digitalization tools are available due to recent advanced technologies including, cloud computing, IIoT, and edge analytics (automation).
Digitalization is viewed as the means to achieve AI, ML, and more. Should energy and processing/manufacturing companies be bothered with such tasks? According to a Wood Mackenzie report, “Digitalization is not a choice to do it or not; it’s about the speed and breadth of adoption.”2 More importantly, digitalization is an opportunity to:
- Reduce operational and maintenance costs
- Optimize equipment/process/manufacturing operations—reduce unscheduled downtime and outages and decrease off-spec (waste production)
- Increase margins (profits)
- Fine-tune capital allocations
- Improve HSE.
Wood Mackenzie estimates that about US$150 billion of annual savings are possible for the energy (upstream and downstream) and mining-metals industries. As shown in Figure 1, the potential savings can be as much as 10% of the operator budget. Several upstream companies have successfully used edge analytics and IIoT data to reduce drilling spending by $20 billion or 10% of their budget.2
Figure 2. The IIoT evolution for various industries.3 Source: IHS Market; copyright IHS Markit 2017, all rights reserved.The savings possible through digitalization are measurable and quantifiable. Yet, the energy industry has not fully embraced it and is very conservative in adopting emerging technologies. As illustrated in Figure 2, the energy industry has expanded data collection but still struggles on connectivity issues.2 In contrast, the chemicals industry is ahead in adopting IIoT.3
Digitalization will be the new normal for businesses. Greater pressure will be placed on companies to move their business models to fully utilize process/system data in decision-making. More importantly, Wall Street and investors are keenly aware about AI, ML, digitalization, and the benefits attainable through these developments.
The digital age is here, and the tools to reinvent businesses have arrived.
1International Energy Agency, “Digitalization and Energy,” Nov. 5, 2017.
2 Wood Mackenzie, “Digitalisation and the race to work smarter,” 2018.
3Howell, J., “The industrial Internet of Things is here, but widespread adoption remains elusive,” Nov. 10, 2017, IHS Markit.com.