Siemens and SAP IIoT Partnership

The relationship between original equipment manufacturers (OEMs) and manufacturing end-users is undergoing a sea change in terms of how equipment is purchased and maintained. Numerous forces are responsible for this shift. Most prominent among these is the availability of fewer onsite engineers. This operating reality has led manufacturers to outsource much of their maintenance operations, requiring them to rely more heavily on remote condition monitoring and predictive maintenance techniques provided by OEMs themselves.

As a result, new business models, bolstered by digital transformation, have begun to spring up among OEMs. For instance, performance-based costing, which bills end-users based on the amount of throughput a machine achieves, has started to usurp the flat-fee model. This not only reduces upfront capital expenditures for manufacturers, but incentivizes OEMs to continuously improve the performance of their equipment, making them more competitive and delivering better results for end-users.

Watch this video for more on how the "as-a-service" model is changing automation technology purchases.

In addition, as these machines-as-a-service type arrangements become more prevalent, they are being tapped to provide an end-to-end data pipeline between OEMs and end-users that allows those who design and engineer equipment to better understand how their products are used in the field, effectively extending the process of asset lifecycle management to the planning and design stage of a piece of machinery.

These new partnerships between OEMs and manufacturers are increasingly being made possible by partnerships between OEMs and providers of industrial software. One such example is the recent expansion of a partnership between Siemens and SAP, wherein Siemens will begin offering SAP’s Asset Intelligence Network, the SAP Asset Strategy and Performance Management Application, and the SAP Enterprise Portfolio and Product Management package. In turn, SAP will offer Siemens’ Teamcenter software service lifecycle management portfolio.

SAP’s Asset Intelligence Network and its accompanying applications allow end-users to collect and aggregate sensor, time series, and status data from equipment into a centralized repository that can be used to build a digital twin for sharing with others—in this case, an OEM. By studying the digital twin, OEMs will not only make suggestions for maintenance and improving performance, but will be able to learn more about how their equipment is actually used in the field to improve the design of future products.

Supporting this data sharing process, Siemens’ Teamcenter software enables engineers to share computer-aided design (CAD) and design data via the cloud for real-time, remote collaboration at the product development stage. Users can view, measure, and markup CAD files, share projects, and review designs via augmented reality on tablets and other mobile devices.

According to SAP and Siemens, the integration of this diverse set of offerings will bolster collaboration across the entire supply chain, offering OEMs and manufacturers alike the possibility to discover end-to-end efficiencies that previously would not have been possible. By using SAP’s Asset Intelligence Network and Siemens’ Teamcenter software together, the companies contend that a consistent digital twin of a plant’s operation can be viewed by plant operators, OEM service teams, and engineers working in new product development.

“Siemens is helping industrial companies make more confident decisions by closing the loop between IT and OT,” said Cedrik Neike, member of the managing board of Siemens and CEO of Siemens Digital Industries. “Through this partnership, we are enabling a true digital thread that integrates real time operations-based data with virtual product and asset models using components from both Siemens and SAP to provide operational insights. This can accelerate digital transformation for industrial equipment owners, operators, and manufacturers who can offer new business models including performance and usage-based cost, and to more efficiently use assets.”