How Siemens addresses increasing complexity in manufacturing – my key takeaways from the Siemens Media and Analyst Conference 2019

On September 4-6, 2019, the software division of Siemens Digital Industries held its media and analyst conference in Brooklyn, New York. For this event, Siemens invited around 100 analysts and media representatives to give an update on their strategy and achievements. Here are my key takeaways.

Within the software division of Digital Industries, Siemens markets its portfolio of industrial software comprising PLM (incl. CAx), EDA, MOM, performance analytics software, and rapid application development tools. The core theme at this event was that with its industrial software portfolio, Siemens aims at helping its customers to address the increasing complexity in the engineering and manufacturing domains.

Personally, I believe that the increasing complexity in engineering and manufacturing is a result of ever-faster changing market demand and increasingly complex customer requirements, to which manufacturers have to respond accordingly in order to stay competitive in the long run. On the one hand, this impacts how manufacturers design and engineer products, and on the other hand, it has an impact on how flexible and agile they are in producing products.

From Siemens’ point of view, this complexity can be addressed by manufacturers – among others – by leveraging digital twins and by adopting personalization approaches.

Digital twins to control and manage complexity

From my perspective, the digital twins concept in general is hardly new, but Tony Hemmelgarn, CEO of Siemens Digital Industries Software, put it nicely in his opening presentation: “…the value of a digital twin increases the more the physical model is connected with its digital model...”. And IoT will play a major role in achieving this. This is because IoT will be the key enabler in enriching digital models, for example with real-life operating data from a physical asset. Therefore, the further development of Siemens MindSphere, the company’s IoT platform, is of great strategic relevance to Siemens as it enables manufacturers to build IoT-enabled digital twins. Digital twins of a manufacturer’s production lines, plants, and production processes, for example, will be the key to controlling and managing production complexity.

Personalization approaches to reduce complexity

For Siemens, adopting personalization approaches to address complexity is, among other things, about leveraging the capabilities of recently acquired Mendix and additive manufacturing as well as machine learning applied to engineering processes:

  • Among the most important messages from this event is that Siemens aims at positioning its low-code application platform, Mendix, as a layer to be put on top of any existing application landscape, including Siemens and non-Siemens applications (e.g. SAP, Oracle, Salesforce, etc.) to develop personalized applications. A statement that makes this very clear came from Derek Roos, CEO of Mendix: “Siemens is committed to opening its entire portfolio through APIs that can be discovered and consumed using Mendix…”.
  • Additive manufacturing is another way of addressing increasing demand for personalization. Besides its Additive Manufacturing Network, which was announced in 2018, Siemens is currently working on solutions that automate the discovery of optimal lattice structures or designs of 3D printed parts and use artificial intelligence and machine learning to accelerate and automate those optimized designs to meet functional requirements. Furthermore, machine learning is used to model and predict the fatigue life of parts that have been produced via added manufacturing.
    From teknowlogy’s point of view, the major benefit of additive manufacturing is that it allows manufacturers to optimize component shapes as well as produce lightweight designs and create lightweight hollow structures, which cannot be produced with traditional engineering and production methods. Plus, the growing maturity of additive manufacturing technologies will also drive investments in AI and ML-enabled design and engineering applications. For Siemens, investing in AI and ML-enabled design and engineering applications as well as additive manufacturing makes sense in terms of market growth on the one hand, and is a natural step on the other, given Siemens’ strong background in production technology and strong analytics know-how.

Another major topic throughout the entire event was Siemens’ IoT operating system, MindSphere. News related to MindSphere were, among other things, the release of a solution that enables cross-tenant data sharing and a solution that allows customers to upload not only machine data that fits into time series but also other documents. And as more and more analytics will be required at the shop-floor level (e.g. to run predictive quality controls), this requires analytics to be run at the edge. For this purpose, Siemens announced the MindSphere open edge framework, which allows the MindConnect boxes to become intelligent by adding analytics managed out of the cloud. Interestingly, Siemens is leveraging its partnership with SAS, which was announced at Hanover Fair in 2019, as a white-label solution in MindSphere for streaming analytics.

I’ve talked to many manufacturing companies over the past 12 months and have learned that in some cases there is a huge skill gap with regard to analyzing data from the shop floor. This means that being able to technically capture data by using IoT platforms is not the main success factor here. Instead, appropriate measures need to be taken to turn this data into valuable insights. These insights are of particular value if a business case can be created around it. This is why, prior to kicking off IoT projects, a related business case has to be built. In our view, there is considerable demand for consulting in creating use cases backed by a business case.

It remains to be seen how Siemens will address this demand in the future. At Hanover Fair in April 2019, Siemens announced efforts to establish an IoT consulting unit, but it seems that this will still take some more time.

Beyond MindSphere, Mendix, digital twins, and additive manufacturing, many more updates were given during the event. Please also refer to my tweets during the event on Twitter.

The topics mentioned in this blog post only reflect some of the aspects that I found particularly interesting. For further details on our view on Siemens Digital Industries Software, please also refer to our company profile and stay tuned for an update of this profile.

Moreover, please also refer to our PAC RADAR vendor evaluation “IoT platforms for industrial applications”, which includes an assessment of Siemens MindSphere.