- Companies need to evolve to take advantage of big data analytics, IoT to drive greater productivity
- New approaches needed to address the increased security challenges in the IoT age
IF INNOVATION in the 18th century was driven by the needs of the industrial revolution, the technological breakthroughs of today belong to the digital industrial revolution.
General Electric (GE) Digital chief commercial officer Mark Sheppard (pic, above) believes that in this age, the implementation of the Internet of Things (IoT) means that more machines will be connected to the Internet, offering users real-time analytical insights that can generate greater productivity and cost savings.
“We are in this new era where the digital equation plays a factor in the company’s operations. That is radically changing our company,” he said at the company’s Digital Advantage Conference in Kuala Lumpur.
Consumer Internet has been around for the last 20 years, said Sheppard, and it is so ubiquitous in our lives with everyone connected all the time. That’s however not true in the industrial space as companies are just starting to connect their equipment to the Internet.
He said GE is becoming a digital company and it is increasingly imperative to understand the equipment that they are selling as well as the software that drives it.
This need has led to the formation of GE Digital, a division with a 13,000 strong workforce comprising of software engineers from different software teams.
“Rather than each business building its own software, we built Predix, a cloud-based operating system for the industrial Internet or industrial IoT,” said Sheppard.
He added that there has been overwhelming customer demand to make their machines work harder and more efficiently.
“It's a great platform for pulling data, analysing that data and presenting it in a format that looks presentable for you and your customer to view,” he said.
He explained that Predix can help companies gain insights into the condition of its assets and perform predictive maintenance on them before they break down.
In the same way, it would also be able to prevent unnecessary downtime by using analytics to factor in weather data and temperature bearings to model the journey of a freight train and make an informed decision if it would derail due to adverse weather conditions.
Petronas Downstream chief information officer Kevin Chong couldn’t agree more with Sheppard that predictive analytics is crucial to ensure minimum downtime that could cost millions of dollars in lost revenue.
“Gone are the days of having a maintenance schedule. Having the predictive capability will not only help us avoid shutdowns but also plan the entire supply chain better by ordering the replacement parts in advance before a breakdown,” he said.
Chong detailed the complexity of Petronas’ oil and gas operations where it takes a series of machines to process crude oil into a useable end product.
“Previously the awareness of IoT was very low in the company but we as an organisation need to restructure and be more agile. This is especially true as we target a 20% improvement in our operations over the next five years,” he said.
Sheppard feels that the role of the data scientist is increasingly important. “Software alone would only give you a picture of what is happening but to turn it into reality you need a good data scientist to understand the machine and the practicalities of the landscape that they are involved in.”
Challenges of securing the industrial Internet
As more machines and devices get connected to the Internet, enterprises have to keep in mind that they are exposed to more risks and threats.
GE Digital solutions architect Rajiv Niles (pic, above) is of the opinion that critical infrastructure are not still not well protected because there is a misconception that the industrial control system is airtight with no external network access.
“We are really only at the awareness stage now when we should be at the mitigation phase. We should be having mitigation strategies put in place,” he said.
But the scary truth is that no one is safe and there are always ways to exploit a system. Given a short amount of time hackers can learn ways to get in and take control of a system.
“One year I was at the Defcon Hacking Conference in Las Vegas and there was a session where a group of hackers were tasked to hack into an industrial control system. Most of them had never seen such a system before but with just a brief training session, one hacker actually managed gain full control within 20 minutes,” he told.
One challenge facing enterprises today is that IT and Operation Technology (OT) are converging and that means there is a larger ecosystem to protect.
To match this challenge, security providers today have to come up with new approaches to counter hackers.
“One of the areas we see a lot happening in is the field of artificial intelligence (AI). That's something that clearly applies to IoT,” said Nikhil Batra, research manager at IDC Asia-Pacific.
“There are unicorns out of Silicon Valley and China who are working on AI-specific solutions which help you detect a malware not based on a standard definition file but using self-learning systems,” said Nikhil.
Rajiv concurs that using AI methods to capture output data, intelligently learn hacker behaviour and report on anything strange will help them monitor large systems with huge amounts of data.
All enterprises and MNCs are struggling to now find the best way to cope with this.
“Hence it is up to the vendors, community and service providers to get together to offer a next-generation solution. It is not just about offering endpoint protection, there needs to be an end-to-end solution to protect the entire ecosystem,” said Nikhil.
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