What happens next? Maintenance must transform if manufacturers are to meet their Industry 4.0 goals
Businesses need to act now to evaluate how new technologies fit into their long-term manufacturing strategies and capitalise on these developments – or risk getting stuck on the wrong side of disruption. Kevin Bull, Product Strategy Director, Columbus UK, explains how predictive maintenance is transforming manufacturing and which technologies businesses need to focus on to stay ahead of the competition.
There is a huge push towards Industry 4.0 with manufacturers of all sizes looking to embrace emerging technologies such as AI, machine learning and advanced data analytics as part of their digital transformation. In our recently published ‘Manufacturing 2020’ report, companies cited production flexibility, reduced costs and increased output as the long-term benefits of improved factory connectivity. The evolution of asset maintenance is going to play a big role in achieving these goals.
Developing an IoT vision of manufacturing
Industrial IoT (IIoT) provides the framework on which further disruptive technologies can build and contribute to improved maintenance practices. IIoT deployments monitoring temperatures, vibrations or humidity from sensors embedded within equipment on the plant floor, all generate large volumes of data in real-time. This is uncovering new insights into processes and sub-processes we’ve never been able to capture before and dramatically changing how we schedule and predict maintenance requirements.
Once this data is gathered in a cloud-based system, it can be analysed to identify equipment status, monitor efficiency and detect if components are failing. Achieving this would put an organization on the digital transformation map. However, to get ahead of the competition, they will need to think ahead too. They can’t predict where the next production bottleneck will develop, or which would be the most cost-effective way to organize maintenance for a fault they can’t see – but machines can.
Predictive maintenance is always learning
As more manufacturers embrace IIoT, new opportunities are created for maintenance to move from a traditional reactive to a predictive model and start to have a positive impact on equipment uptime and production quality. With reactive maintenance, if equipment unexpectedly goes offline as a result of failure, the damage to productivity has already been done and creates a knock-on effect further down the production chain. In contrast, predictive maintenance strikes a balance between reactive and excessive maintenance, identifying and resolving potential issues before equipment breaks down without incurring excessive costs from emergency or even over-maintenance.
AI and machine learning represent another step towards truly predictive maintenance. When unleashed on the vast volumes of data captured from the plant floor, data analytics can be enhanced to filter out anomalous information, detect hidden or underlying patterns and more accurately project equipment reliability – and adjust maintenance schedules accordingly.
Data is the lifeblood of digital transformation
Advanced data analytics will be key to identifying any ‘teething problems’ when deploying new, fully digitised equipment and systems. Analysing the effectiveness of emerging technologies and how they affect existing business processes can help future-proof businesses against further digital disruption and manage the impact of newly-deployed solutions.
The benefits of improved data analytics capabilities become immediately apparent across multiple business processes. This was the case when Domino Printing Sciences updated their enterprise systems to accommodate more data-driven business insights. “We are using live data in the manufacturing process to drive improvements in yield through automated test equipment. It removes subjective human assessment and poke-yokes the product at each stage rather than fixing at the end of the process”, said Carl Haycock, UK printer operations director.
Combined with machine learning, data analytics can help improve the availability, uptime and lifetime of assets – helping organizations cut costs, improve operational efficiencies and rely on data-driven decision making. When harnessed correctly, these disruptive technologies will deliver wider business benefits for manufacturers, from shop floor and the customer experience to service delivery models.
By Kevin Bull, Product Strategy Director, Columbus UK
Siemens: Providing the First Industrial 5G Router
Across a number of industry sectors, there’s a growing need for both local wireless connectivity and remote access to machines and plants. In both of these cases, communication is, more often than not, over a long distance. Public wireless data networks can be used to enable this connectivity, both nationally and internationally, which makes the new 5G network mainframe an absolutely vital element of remote access and remote servicing solutions as we move into the interconnected age.
Siemens Enables 5G IIoT
The eagerly awaited Scalance MUM856-1, Siemens’ very first industrial 5G router, is officially available to organisations. The device has the ability to connect all local industrial applications to the public 5G, 4G (LTE), and 3G (UMTS) mobile wireless networks ─ allowing companies to embrace the long-awaited Industrial Internet of Things (IIoT).
The router can be used to remotely monitor and service plants, machines, as well as control elements and other industrial devices via a public 5G network ─ flexibly and with high data rates. Something that has been in incredibly high demand after being teased by the leading network providers for years.
Scalance MUM856-1 at a Glance
- Scalance MUM856-1 connects local industrial applications to public 5G, 4G, and 3G mobile wireless networks
- The router supports future-oriented applications such as remote access via public 5G networks or the connection of mobile devices such as automated guided vehicles in industry
- A robust version in IP65 housing for use outside the control cabinet
- Prototypes of Siemens 5G infrastructure for private networks already in use at several sites
“To ensure the powerful connection of Ethernet-based subnetworks and automation devices, the Scalance MUM856-1 supports Release 15 of the 5G standard. The device offers high bandwidths of up to 1000 Mbps for the downlink and up to 500 Mbps for the uplink – providing high data rates for data-intensive applications such as the remote implementation of firmware updates. Thanks to IPv6 support, the devices can also be implemented in modern communication networks.
Various security functions are included to monitor data traffic and protect against unauthorised access: for example, an integrated firewall and authentication of communication devices and encryption of data transmission via VPN. If there is no available 5G network, the device switches automatically to 4G or 3G networks. The first release version of the router has an EU radio license; other versions with different licenses are in preparation. With the Sinema Remote Connect management platform for VPN connections, users can access remote plants or machines easily and securely – even if they are integrated in other networks. The software also offers easy management and autoconfiguration of the devices,” Siemens said.
Preparing for a 5G-oriented Future
Siemens has announced that the new router can also be integrated into private 5G networks. This means that the Scalance MUM856-1 is, essentially, future-proofed when it comes to 5G adaptability; it supports future-oriented applications, including ‘mobile robots in manufacturing, autonomous vehicles in logistics or augmented reality applications for service technicians.’
And, for use on sites where conditions are a little harsher, Siemens has given the router robust IP65 housing ─ it’s “dust tight”, waterproof, and immersion-proofed.
The first release version of the router has an EU radio license; other versions with different licenses are in preparation. “With the Sinema Remote Connect management platform for VPN connections, users can access remote plants or machines easily and securely – even if they are integrated in other networks. The software also offers easy management and auto-configuration of the devices,” Siemens added.