Scale up this scenario a thousand times and the losses from unplanned downtime would definitely be huge. Fortunately, with the industrial Internet and Internet of Things (IoT), we can pre-empt breakdowns and even seek options to improve efficiency by harnessing data and converting them to insights.
GE Digital Chief Commercial Officer Mark Sheppard told the audience at the GE Digital Advantage Conference 2016 in Kuala Lumpur that an improvement of 1% can go a long way in increasing margins or minimising losses.
“We like to draw reference to the power of 1%. In the Oil and Gas industry, an extra 1% uptime would bring about an annual impact of USD5 billion to USD7 billion. In transportation, by travelling 1mph faster, the annual impact is USD1 billion to USD2 billion.
“Similarly, if airlines improve fuel efficiency by 1%, they could save USD2 billion to USD3 billion per year. The same applies to utility companies, who could save USD4 billion to USD5 billion. For healthcare, an increase of 1% productivity would bring about an annual impact of USD4 billion to USD5 billion,” he said.
It is not easy to achieve this 1%, but it is more achievable with the digital industrial evolution.
“We have millions of sensors and a lot of data, and in the past, we did not make enough use of them.
“Now, we have created a cloud system called Predix, and this allows us to develop applications based on this platform,” said GE ASEAN President and CEO Wouter Van Wersch.
Van Wersch said that GE is constantly seeking ways to improve efficiency and productivity for its clients.
“Through our GE Store, we have a network of nine research centres in the world, and they are driven by 4,000 experts who are constantly seeking solutions to serve our customers better,” he said.
Malaysia’s national petroleum company, Petronas, shares the view on the significance of improving efficiency, particularly during this period of volatile crude oil prices.
Petronas Downstream Chief Information Officer Kevin Chong said as an integrated O&G company, Petronas not only extract and process oil, but distributes the end-product to consumers as well.
“A price drop of 1% will have an impact of USD1 billion,” he said.
Chong said by gathering more data and converting them to meaningful insights – through methods such as machine learning and cognitive technology – operators would be better placed to make commercial and operational decisions.
“Our target is to improve by 20% over the next five years. As a result, our plants will have to be more efficient and we expect to get better price margins from customers,” he said.
Besides O&G, Sheppard shared that Predix could also be used in the transportation industry to optimise maintenance budgets.
“If you run a fleet of 1,000 trucks, scheduled maintenance is the easiest to perform. At every 8,000km, a component has to be changed. But you do wonder, can the trucks do 9,000km without any trouble? Or will some trucks break down at 7,500km?
“With predictive technology, we would be able to tell you that Trucks 1, 2 and 3 are running well and can continue being on the road, but while Truck 4 needs to come in to the workshop immediately,” he said.