How the industrial internet can drive analytical efficiencies

What we can learn from the oil and gas industry?

Oil rig

Since the dawn of the computer age, one of the biggest challenges has been getting different operating systems and programming languages to work with each other. With the rise of the internet of things, how can we make sure the “things” can talk to each other?

General Electric (GE) hopes that its cloud-based Predix platform could be the answer. Launched in 2015, this platform as a service (PaaS) software is intended to facilitate the introduction of connected devices across the industrial internet, by providing a standard way to connect data, machines and people to drive powerful new analytical approaches.

GE hopes the power and flexibility of the platform will enable users to develop applications that could dramatically improve efficiency across industries. As GE gains more experience of the software, it will be able to transfer great ideas from one sector to another, creating dramatic efficiencies to transform industries, including oil and gas, power and water, manufacturing, mining, health care, transportation, aviation and more.


The rising return on investment of data analytics

Predix may have come out of the development of an internal internet of things operating system, designed by GE engineers for its own machine data collection and analysis, but its origins go back 20 years – when crude oil prices were low and technology costs were relatively high. Back then, companies lacked incentives to invest in systems that would boost efficiency. When crude prices rose dramatically, market forces pushed the oil industry to find new reserves, at the expense of high efficiency.

In the past year and a half, oil prices have again declined. But this time, so has the cost of technology, so the potential ROI for digital technologies and analytics has become attractive. The added pressure on oil and gas firms to improve the profitability of their operations has turned this into an ideal time for the industry to implement digital technologies and analytics.

In the current environment, for example, a one-percentage-point increase in the productivity of existing assets can make a huge difference to oil producers’ bottom lines. And it is here where the industrial internet can really deliver.

Oil rig

Focusing on productivity

GE focuses its multilayered approach on improving productivity by tackling the oil and gas industry’s core issue of high production costs. It starts by installing sensors on the machines it makes, as well as those of others. These collect and analyze data on all rotating and static equipment, and can provide valuable information about wear and tear, so that maintenance or replacement can be predicted and scheduled to reduce downtime. 

If a valve fails, for example, it can shut down a US$10 million gas turbine. And preventing the failure of a small part in a big rig can also save millions in production time.


Making it easier to find insights

The Predix platform also holds the potential for GE to ease the adoption of new business processes by end users, making it easier for non-specialists to generate insights from data. One application offered through the platform is a real-time visual representation of pipeline risks. Its user interface is based on familiar consumer applications used on mobile devices, which makes them easy to use, facilitating faster technology adoption so that the financial benefits of analytics can be generated quickly.

Predix gives business leaders a way to prove the value of an analytics project through pilot testing. In an industry where an engineering culture is predominant, evidence-based analytics applications are very useful from an adoption perspective. This is particularly relevant in the oil and gas industry, where the high-risk and reward nature of the business means downtime is excruciatingly expensive, and safety is paramount.


Moving from insight to understanding

In the big data age, the oil and gas industry has tremendous opportunities to gain productivity through initiatives such as the industrial internet – and its current pressures mean it is pushing ahead fast, so other industries should keep a close eye on its progress.

But, as with other analytics efforts, it takes more than stellar technology offerings. It means understanding how to make the most of the data these new technologies are generating, and how to reach and persuade decision-makers who will choose whether to adopt these business-changing systems.


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