Taking the edge off Industry 4.0

??Gartner predicts that, by 2025, more than 75 per cent of enterprise-generated data will be created and processed outside the traditional data center or cloud. Gaining access to relevant data in a central location, either a cloud or a data center, is key to making changes and meeting business objectives. Companies must therefore ensure data is received in a faster, more secure and cost-effective way by making edge analytics a key part of their IIoT strategy.

Edge analytics is the collection, processing and analysis of data either at, or close to, the source of the machine or other connected device, at the edge of the network.

Big technology giants are aware of edge analytics’ advantages, and are investing in the area. Apple acquired the startup, Xnor.ai, which uses artificial intelligence (AI) to run deep learning analytics models on edge devices like phones, cameras and drones. Google Cloud and Amazon AWS have also developed edge IoT-focused products. Now, as they seek to improve processes and adopt Industry 4.0 technologies, manufacturers are also taking note.

Edge systems hold numerous benefits for the manufacturing industry. Relevant data can be transmitted from the edge so that businesses can act on insights in real-time. The reduced distance between the server and end-user enables quicker data analysis and decision-making.

In addition to delivering faster insights, the sheer volume of data that connected devices are creating is making edge analytics a necessity. According to International Data Corporation (IDC), “every connected person in the world will have at least one digital data interaction every 18 seconds , from one of the billions of IoT devices, which are expected to generate over 90 zettabytes (ZB) of data in 2025”. Now, if we consider just how many IIoT devices are available in a smart manufacturing plant, we can quickly see why manufacturing needs the edge.

Strategy on the edge

Manufacturers must manage all their devices while maintaining a competitive edge, and in ways that complement how a plant operates. This is where edge analytics can play a vital role in helping manufacturers to meet organisational objectives — but how?

Numerous devices can benefit from edge analytics in Industry 4.0 environments, like smart factories. Digitalised plants rely increasingly on embedded sensors throughout the production line, connected robots on the factory floor and devices that monitor safety conditions. Each device generates critical data that needs processing and should be acted upon to support lean and efficient operations.

Specifically, edge analytics can play a crucial role in monitoring asset performance in Industry 4.0 scenarios. The fast data analysis made possible by edge systems can help to prevent equipment failures and disruption to production lines. Moreover, edge systems can help maximise efficiency and costs.

Take for example equipment health. Edge analytics can be used to aid condition-based maintenance (CBM), which uses sensor data to assess equipment heath. Insights from the equipment are sent back to a central location, at a speed much faster than any cloud solution can provide, enabling plant managers to instantly react and devise a maintenance strategy.

Using edge analytics in this manner can reduce equipment failures and save costs. In fact, it is estimated companies can recover as much as half their annual maintenance budget by aligning maintenance investment to asset condition.

Besides this, costs of central data storage, transmission and management are reduced as there’s less data stored centrally. Lastly, edge analytics improves security and privacy compared to centralised cloud providers, as the data is less likely to be intercepted

Edge analytics is also versatile enough so that any type or age of plant can adopt the technology. For example, edge analytics is also used to harmonise data, which means different datasets are converted into a common format for machine compatibility. This is ideal for factories with legacy equipment that collects data in different ways, ensuring all devices — old or new — are incorporated into the edge system.

Uncovering equipment data

One manufacturer that has benefited from edge analytics software is Rubble Master, which specialises mobile equipment for the mineral processing industry.

Rubble Master sought to do more with its data from more than 4,000 machines that it operates around the world. In particular, Rubble Master wanted edge software that would allow its fleet to collect, filter and store data to help its machine operators to gain valuable insights into machine health and status, and better connect with end users. For this, it turned to Crosser, specifically its low-code platform for streaming analytics.

?In the end, Rubble Master was satisfied with Crosser’s software, complementing its “efficiency, reliability and flexibility.” In the words of Markus Gaggl, Chief Technology Officer (CTO) at Rubble Master, “We believe edge analytics is key to uncovering equipment data.” Because it helps manufacturers realise these benefits through edge software, Crosser was recently named one of the Top 5 Edge Analytics Start-Ups in the world by Start Us Insights.

As recently as two years ago, it was only imagined that edge analytics could improve manufacturers’ ability to meet their IIoT objectives. It’s now clear that edge analytics can support manufacturers’ IIoT strategies as more companies like Rubble Master — and big tech players, like Apple and Amazon — get onboard. By getting closer to the edge, manufacturers can gain faster insights into their processes and manage quicker and more efficient production operations.