Siemens, IBM and Red Hat are working together to provide manufacturers and plant operators with an open, flexible and more secure solution to increase the usability of real-time operational data. What does this collaboration look like?

Marilies Rumpold-Preining: The joint initiative enables Siemens MindSphere to run on the Red Hat OpenShift platform. This allows companies using MindSphere to take advantage of a hybrid cloud architecture and Kubernetes technology. This makes it easier to establish the IoT solution at different locations and increases the speed and agility of operations. At the same time, it complies with very strict data privacy rules, such as those required in the pharmaceutical or medical sector, as the solution can be operated in a private cloud with OpenShift and is not tied to a public cloud.

Use cases that require low latency times for data access are supported, as is use in remote locations or locations subject to extreme loads. Large volumes of data can be processed locally and do not have to be uploaded to a public cloud, which can also mean cost benefits. The prompt processing and analysis of sensor data and other information means that problems can be identified and dealt with at an early stage. A combination of private cloud and the use of public cloud services is possible at any time thanks to the hybrid cloud approach. Data can be used on site or made available in the public cloud via the 'Services' container platform.

Marilies Rumpold-Preining, Director Red Hat Synergy at IBM.

© IBM

What prospects arise from the collaboration? For the partners, but also for the industries?

Marilies Rumpold-Preining: Customers choose their partner for a local implementation of the MindSphere solution and various operating models are available - from operation by in-house IT to complete operation by a partner such as IBM or Siemens. Collaboration between companies and the development and use of services is facilitated by the use of container technology.

Can you explain practical applications of Siemens MindSphere on OpenShift 'on premise' or 'on the edge'?

Marilies Rumpold-Preining: By running Siemens MindSphere on Red Hat OpenShift, the data can be used locally on a private cloud; it can be pre-processed and selected locally. Machine learning is a good application example: Very large amounts of data are generated here that are not shared via the cloud, but are only required locally. The data can be quickly processed and made available in a private cloud at the 'edge', where it originates. Edge technology also means that users are not tied to one cloud provider, but can host their data wherever it suits them best from a technical perspective or seems most secure. They are also able to use data-intensive applications such as video analysis in spatially separated environments, such as office buildings or retail spaces. For example, cameras and sensors in manufacturing can be analyzed in near real-time to help improve quality and safety by detecting when surfaces were last cleaned, if a machine is getting too hot or if a device is malfunctioning.

Since the outbreak of the pandemic, manufacturing processes in industry have had to be rethought. In your opinion, where is the area of data generation and real-time data analysis heading?

Marilies Rumpold-Preining: Data generation and the use of this data are playing an increasingly important role in the IIoT environment. It is important to organize and analyze enormous data flows in compliance with data protection regulations, but also to protect them from unauthorized access and hackers. According to our research, a single production site already generates more than 2,200 terabytes of data per month, most of which has so far remained unanalyzed. In future, this data can be used, for example, to further optimize production, for predictive maintenance and to detect errors in the production process. In automated factories and processes in particular, latency times also need to be taken into account. Keyword speed and security: in future, companies will increasingly consider whether data needs to be stored in the cloud for analysis or whether processing directly at the edge is sufficient, which is possible with new edge technologies and hybrid cloud approaches.

Which cloud solution for which application?

New possibilities through quantum computing.

© IBM

More and more SMEs seem to be approaching the topic of the cloud. There is probably no patent solution as to which cloud is best for whom, but can you give us a brief assessment of the approach?

Marilies Rumpold-Preining : SMEs are not starting from scratch, they have built up systems and processes over the years and - as you say - there is no patent solution. Due to the pandemic, the need to work from home and the acceleration of digitalization, we are seeing increased demand for public cloud solutions - including from SMEs. An easy way to get started is to obtain computing power, bandwidth and individual applications via the cloud as an 'as-a-service' solution. In technical terms, use is via application interfaces, so-called APIs, which connect the company with the application; billing is usually based on consumption, for example in the form of data volume or time usage. Popular entry-level projects are in the area of customer service, for example with chatbots. The portfolio of technologies is growing continuously and access is very direct: on IBM's cloud website, for example, users only need a few clicks before they can start a free trial.

But cloud technologies also offer advantages for core applications for SMEs: If SAP components are used, the migration to SAP S/4HANA will also make it important for smaller companies to remove their individual system customizations from SAP, keyword: 'keep the core clean'. Here, container technology offers opportunities to flexibly implement additional functionality as a microservice and connect it to the SAP functionality via interfaces. The Red Hat OpenShift platform offers broad support in the development and operation of services. Public cloud offerings and hybrid cloud technologies such as Kubernetes make the path to innovation for SMEs more direct and versatile than ever before.

Location-bound or rather borderless? Can you briefly explain the new IBM Cloud Satellite technology and which industrial customers it is suitable for? What are the connections between Cloud Sateillite and Edge Computing?

Marilies Rumpold-Preining: IBM Cloud Satellite enables customers to operate the cloud securely in any environment - in the public cloud, private cloud or even on site at the edge, so to speak. In this way, customers can bring the cloud into their own data center and benefit from cloud services and optimized operation without the data leaving their own data center. This is a major advantage, particularly for companies in highly regulated sectors such as telecommunications, financial services, healthcare or public authorities. Mainz University Medical Center, for example, uses Cloud Satellite to digitalize processes in the hospital environment. Together with IBM, the University Medical Center has developed several new solutions that facilitate the secure exchange of health data and optimize processes for COVID-19 testing and vaccination logistics, among other things. The hybrid cloud approach in combination with IBM Cloud Satellite enables the Mainz University Medical Center to use public cloud services for the development of the solutions, but to keep the data in the data center and thus meet security and regulatory requirements. The hardware and data are always under the control of the University Medical Center.

Cloud Satellite can also be used 'on the edge' where no data center is available. By installing it on a computer in a train carriage, for example, to process sensor data and other information from the train, cloud services can be used securely in completely new locations.

IBM recently launched the most powerful quantum computer in Europe. What opportunities does this open up? How will this change data processing with the cloud as an enabler solution? Keyword Kubernetes and containerization.

Marilies Rumpold-Preining : Quantum computing allows data to be processed much faster than with conventional methods. However, you first have to understand that quantum computing is a completely different type of processing to conventional computers. If you like, the technology is similar to a probability calculation, as the speed of the systems and the cross-calculation and analysis of data leads to approximate results. It does not follow any binary logic.

In the future, it will be possible to 'outsource' certain calculations as a service to quantum computers and obtain results for complex problems very quickly. With the help of hybrid cloud and container technology, these results can then be securely processed where they are needed.

With the quantum computer that is now available in Germany from the Frauenhofer Institute together with IBM, companies in Germany can now build up expertise in dealing with this new technology and develop initial use cases.

Forum Edge & Cloud Control

Which is better - to store and process data centrally in the cloud or decentrally at the edge in production? The Edge & Cloud Control forum at Computer&AUTOMATION addresses precisely this issue: in automation and user jargon, the forum highlights the current trends and developments in data handling for industrial applications
- from the edge to the cloud.
Our discussion partner Marilies Rumpold-Preining will also be giving a presentation.
Virtual Forum Edge & Cloud Control,
October 20 and 21, 2021