Siemens Mind Sphere2

Collaboration Empowers IIoT Use Cases

Feb. 24, 2021
Siemens, IBM and Red Hat collaborate to launch a hybrid cloud initiative aimed to increase the real-time value of IIoT.

Siemens, IBM and Red Hat recently announced a collaboration to use a hybrid cloud designed to deliver an open, flexible and more secure solution for manufacturers and plant operators to drive real-time value from operational data. In one month, a single manufacturing site can generate more than 2,200 terabytes of data according to a report by IBM – yet most data goes unanalyzed.

Through the joint initiative, Siemens Digital Industries Software will apply IBM’s open hybrid cloud approach, built on Red Hat OpenShift, to extend the deployment flexibility of Siemen’s IIoT offering MindSphere for on-premise deployments. 

“We see that most industrial data is generated outside of IT – in manufacturing operations, supply chains or connected products – yet to leverage digital technologies, manufacturers choose to either send data up to their enterprise cloud, or bring the technology down,” said Manish Chawla, industry general manager, energy, resources and manufacturing at IBM. “Our collaboration with Siemens uses hybrid cloud and is being engineered to deliver manufacturers the best of both worlds: autonomy, speed and control over shopfloor data processed at the edge, as well as seamless connection to the enterprise.”

Chawla connected with IndustryWeek to take a deeper dive on the collaboration.

IW: How has the pandemic impacted the manufacturing industry?

Chawla: The greatest shift has been the rapid acceleration of digital technologies.

Prior to the pandemic, digital transformation was still largely experimental. Many manufacturers had integrated apps or software to monitor operations or pull historical analyses on output and efficiency. However, it was predominantly an extension rather than a critical part of their operations.

With the onset of COVID-19, everything from the supply chain, to operations, to employee communication and safety had to be reimagined. Adoption of digital technologies to aid in reinventing these workflows accelerated; what likely would have been a transformation spread across 3 to 5 years happened within a few months.

The shift isn’t temporary. We’re seeing companies that have invested in technology consistently outperform their less tech-savvy peers by 6 points across industries. A similar analysis was done by HBR in 2010 following the 2008 recession, which found that companies that made strategic investments in the future rather just focusing on cost-cutting measures flourished post-recession.

IW: What are you seeing as the biggest challenges manufacturers are facing today?

Chawla: Manufacturers are still expected to produce higher quality products in less time, despite greater strain and challenges to their normal supply chain. This emphasizes the importance of efficiency and accuracy in communicating to their customers.

While technology can aid in both of these demands, ironically, manufacturers struggle because they often have too much existing technology, but need to modernize their operational applications, build integration to get data back to where it can be analyzed and acted on. Most manufacturers are also managing multiple IoT platforms and applications across multiple clouds or locally. This creates a complex and siloed operation. The solve for this is more open technologies that can bring together all the functions and operations across the shop floor as well as tie into the back-end business and data platform. The key is making the IT deployment simpler, so it runs in concert with operations, not as a separate operation to manage. 

IW: Why are Siemens and IBM teaming up, and how does this help address key challenges?

Chawla: We’re collaborating with Siemens and Red Hat to apply IBM’s open hybrid cloud approach, built on Red Hat OpenShift, to extend the deployment flexibility of Mindsphere. This aims to provide manufacturers with an open, flexible and more secure solution for manufacturers and plant operators to drive real-time value from operational data.

This approach offers a flexible architecture that can support a range of use cases and simplifies IT management. For example, in some instances, based on local regulation, competitive risk or data sensitivity, putting data in a public cloud environment is just simply not possible, so a private cloud is needed. Another operation for the same company may leverage a public cloud architecture. The benefit of this collaboration is that all facilities could still run the same applications, with common data governance and a uniform set of principles.

IW: How does this all tie back to edge computing?

Chawla: Edge computing brings the processing power to where the data is generated, rather than the other way around. We find that most of the data generated in manufacturing is most valuable where it was generated. When data has to travel up to the cloud, it creates milliseconds of latency, but even that subtle lag matters. Speed is critical on the factory floor.

With our hybrid cloud approach, we can bring the power of MindSphere down to the factory floor, yet with a common foundation to connect to the enterprise. This is especially important for enterprise manufacturers managing multiple sites, as well as simplifying designing a network for sensors, devices and data.

IW: What type of use cases will this partnership help manufacturers address?

Chawla: A great example of the benefits is energy management and reducing emissions. There is no singular part of an operation that alone is responsible for emissions: there’s energy used to heat and cool a facility, the machinery in the operations line, as well as the supply chain and logistics to produce and distribute goods. With an open, hybrid cloud deployment, operations managers can bring together these data sets to get a holistic view for individual operation sites, or across locations since all data will share a common foundation. 

Another use case is making production quality checks using AI, and then making corrections in real time as the production process is being executed. This is best done when the Industrial IoT platform is operating at the edge rather than in the cloud.

And, there are other companies concerned about data protection and cybersecurity and avoiding sending all their data to a public cloud. We’ve seen a rising volume of threats and attacks on manufacturers. In fact, according to IBM’s latest X-Force Threat Intelligence Index, the manufacturing and energy industries were the most attacked industries in 2020, second only to the finance and insurance sector. Contributing to this was attackers taking advantage of the nearly 50% increase in vulnerabilities in industrial control systems (ICS), which manufacturing and energy both strongly depend on.

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