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What’s required to set up IIoT in manufacturing

What’s required to set up IIoT in manufacturing
In order to make IIoT work effectively, several hardware and software components are needed. While they may be costly at first, the end results can justify the initial investment.
In order to make IIoT work effectively, several hardware and software components are needed. While they may be costly at first, the end results can justify the initial investment.
 
More and more, manufacturers rely on connected devices and the data they generate, collectively known as Industry 4.0 or IIoT, to achieve further production and management efficiencies. To run IIoT effectively, several hardware and software items are needed.
 
“Hardware requirements include devices and equipment that send and receive data and follow the instructions. They generally comprise of chips (microcontrollers, system on chips and RF/communication ICs), development boards and reference design, actuators, interfaces, memories, relays/switches, sensors and transceivers,” said Keshab Panda, CEO and MD of L&T Technology Services. “Software requirements are set of programs which facilitate data collection, storage, processing, analysis, application and instructing to and from IoT hardware components. These comprise of operating systems, middleware or firmware and apps, among others.”
 
Ophir Glazer, VP,
Presenso

In addition, manufactures should also be familiar with the different IIoT protocols, which are formal standards and policies that enable device discovery, identification, multi-layer framework and device management, Panda said. “Some of the most recognized protocols are Wi-Fi, Bluetooth, Fieldbus, BACNet, Ether/IP, LPWAN, 6LowPAN, IPv4/IPv6 and RPL, among others.”
 

Cloud vs. edge computing

 
In terms of the IIoT architecture in a factory setting, cloud and edge computing are typically considered. Each has pros and cons.
 
“Cloud computing advantages include centralization and security of data, and virtually unlimited storage options. The cons associated with cloud computing include strong Internet connectivity requirement and high latency due to low bandwidth connectivity,” Panda said. “Edge computing pros include latency minimization due to reduced distance and network points-of-presence between edge infrastructure and the actual storage location. However edge strategy can be expensive and complex as the upfront investment in implementation and re-skilling is high, and there’s a shortage of developers who can write new apps for emerging edge use cases.”
Keshab Panda, CEO and MD,
L&T Technology Services
 

The best way for manufacturers to implement IIoT, then, is to leverage the advantage of both architectures. “In my opinion, a hybrid approach is suitable for remote locations. In cases of very high volume of data or unique security and compliance requirements, edge is recommended. In other uses cases, cloud is considered the cheapest to deploy,” said Ophir Glazer, VP of Sales at Presenso.

“Both cloud and edge computing will complement rather than replacing each other and it would be up to the businesses to evaluate their requirements and identify how they intend to leverage their devices and the data that is produced by them,” Panda said.
 

More savings down the road

 
Needless to say, implementing IIoT, including the hardware, software and the network infrastructure associated with it, can be a significant investment that can be quite daunting to manufacturers, especially small- and medium-sized ones.
 
However, while the cost of setting up IIoT is a legitimate concern, manufacturers should think the cost-savings IIoT can help achieve through product quality improvement, preventive maintenance and reduced downtime.
 
“We typically conduct business value assessment workshops and calculate the cost of machine failure: unplanned downtime, maintenance repair costs and machine replacement. We then estimate the expected savings by using our solutions, and help the customer make the decision if it’s worth investing in predictive maintenance,” Glazer said.
 
“Now we can know when there's an issue at, for example, a distillery over the weekend. We are not going to come back on a Monday to a surprise, and that's going to save you US$50,000 to $100,000 in productivity,” said Ryan Martin, Principal Analyst at ABI Research. “If it happens once over the course of a year, it’s worth it.”


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