Manufacturing moving from M2M to the IoT; are you ready?

  • Overcoming proprietary protocols in older machines as connectivity grows
  • Sensors can help solve the problem, don’t just throw more manpower at it
Manufacturing moving from M2M to the IoT; are you ready?

 
DIGITAL disruption might be more evident in white-collar industries, but it is also happening within blue-collar industries such as manufacturing.
 
Heavy industries have never been thought of as cutting-edge, but manufacturing was one of the first few users of machine-to-machine (M2M) communications.
 
However, while they may have got a head-start on technology, these industries are now facing challenges with proprietary M2M protocols even as they gear up for the Internet of Things (IoT) future, according to Saj Kumar, IoT vice president at SAP SE.
 
“M2M is fairly old and the IoT is redefining the way we talk to machines,” he says, speaking recently to Digital News Asia (DNA) in Singapore.
 
“The technologies that started with M2M were based on fairly proprietary standards – there were some standards at the hardware and protocol levels but these were driven by select groups.
 
“What you’re seeing with the IoT is that the hardware level is more open because the connection is all-IP (Internet Protocol), which allow us to talk to devices on IP – but we are also seeing machines on the shopfloor moving from proprietary [protocols] to IP.
 
“Eventually, you might get to a stage where everything becomes a thing with an IP address you can start talking to – that way, you can have a standards-based communications protocol to talk with, whether it is an M2M or IoT device,” he adds.
 
This is still in the future though, mainly because factories continue to persist with their current way of doing things.
 
“It’s not easy to replace all these old machines just because you have some new technologies that communicate better,” says Saj.
 
“Manufacturing guys are more interested in ensuring that productivity is up and machines are running and producing, but over a period of time, as they want to modernise the factory, they will have newer machines with IP,” he adds.
 
In essence, factories today are stuck between the proprietary and IP worlds, while needing to connect machines from both eras. Worse, some of these older machines cannot even be connected to.
 
“But what we’re seeing is that some of these machines are being supplemented by sensors, so even if the machine is unable to talk to you, you can able retrofit it with sensors, which allows us to collect data with IP protocols,” says Saj.
 
Then there is the added challenge of connecting the shopfloor without interrupting production, he adds.
 
The manpower panacea
 

Manufacturing moving from M2M to the IoT; are you ready?

 
Turning to machines to solve problems in production might be a huge cost upfront, and factories in Asia might be more inclined to just use manpower to overcome them.
 
Not surprisingly, Saj (pic above) advises against that.
 
“You can throw more people at the problem and not analyse the root cause of it … so it will just happen again,” he says.
 
“[Sensors] allow you to find the root cause using data science, as it is happening, and stop it from happening – which is more valuable,” he adds.
 
The view that labour is cheap in Asia is also a misconception. “It is actually getting expensive in Asia,” says Saj.
 
“Most companies are already operating at very thin margins, and every little bit counts,” he adds.
 
To unlock the insights that the IoT can bring to the shopfloor, manufacturers need to look towards hiring “unusual talent” – that is, people who can understand the data, according to Saj.
 
“Start hiring some data scientists – you need that skill,” he says.
 
“Vendors only know one part of the process, the actual domain expertise is yours – this is an opportunity to retrain some of the younger workforce to understand data,” he adds.
 
Related Stories:
 
How the IoT is transforming traditional industries
 
Manufacturers need a long-term view of IoT: Gartner
 
How Industry 4.0 can transform the manufacturing landscape
 
 
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