Jun 1, 2020

GE Digital: smarter manufacturing with AI & analytics

Cobus van Heerden
3 min
Cobus van Heerden, Senior Product Manager, Analytics & Machine Learning, GE Digital, discusses the current AI and analytics trends in manufacturing...

Cobus van Heerden, Senior Product Manager, Analytics & Machine Learning, GE Digital, discusses the current AI and analytics trends in manufacturing.

What are the current trends within manufacturing when it comes to AI and analytics?

Process engineers have exceptional domain expertise to put together process models – or Process Digital Twins – and be able to interpret the models. This is the foundation for improving competitive advantage and success with analytics.

What are the benefits of AI in manufacturing relating to analytics?

With Machine Learning and analytics, industrial organizations can capitalize on the IoT opportunity, optimize operations, and generate greater profitability. Additionally, engaging in the latest analytics technologies also helps to attract and retain the best talent.

What are the challenges of AI?

All process engineers can and need to develop capabilities in analytics and machine learning to remain competitive – both at an individual professional level as well as to help their industrial organization – in our world of digital transformation.

Over time, engineers can go from small projects to pilots to multi-plant optimization with deep application of analytics. Engineers’ deep domain expertise provides a foundation for modelling processes and developing the analytics that are game changers in very specific applications. The combination of applied analytics technology with those Process Digital Twin models uncovers hidden opportunities for improvement over and over again.

What is the best strategy for driving the best business value from AI and analytics when it comes to analytics?

Fortunately, the journey to success with machine learning and analytics doesn’t mean that process engineers suddenly need to become data scientists. Proven processes and software technologies make analytics achievable for every industrial organization. To support the journey to machine learning and analytics, companies like GE Digital provide analytics technology training in the form of a self-serve product university, detailed demo videos, and application advice.

Additionally, while today’s software features enhanced ease of use and no-code implementation extensible with Python, process engineers can still lean on product experts in combination with their own domain expertise to mine data and leverage analytics to improve operations.

To drive analytics and improve processes, organizations can align domain expertise and strategically drive analytics in five areas: 

  1. Analysis - automatic root cause identification accelerates continuous improvement

  2. Monitoring – early warnings reduce downtime and waste

  3. Prediction – proactive actions improve quality, stability, and reliability

  4. Simulation – what-if simulations accelerate accurate decisions at a lower cost

  5. Optimization – optimal process setpoints improve throughput at acceptable quality by up to 10%

Looking to the future how would you like to see this technology developed within the industry?

Software solutions using advanced AI and machine learning to enable process engineers need to continue to be innovative and outcome oriented. These solutions need to focus on providing the ability to combine data across industrial data sources and rapidly identify problems, discover root causes, and automate actions to continuously improve quality, utilization, productivity, and delivery of production operations.

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Jun 17, 2021

Siemens: Providing the First Industrial 5G Router

Siemens
5G
IIoT
Data
3 min
Siemens’ first industrial 5G router, the Scalancer MUM856-1, is now available and will revolutionise the concept of remote control in industry

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). 

Siemens presents its first industrial 5G router.
Siemens presents the Scalance MUM856-1.

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

 

5G Now

“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.

 

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