OEM&Lieferant Ausgabe 2/2020

106 Automation Manufacturing-as-a-service platforms – so disruptive business models actually exist? By Dr.-Ing. Olaf Sauer, Automation business unit/Deputy Institute Director Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe In the context of increasing digitalization, there are also some concerns about disruption, which means a radical transformation of the existing business landscape as new business models and a completely new range of products and services emerge. In manufacturing and the related automation technology, the changes brought about by Industrie 4.0 resemble an evolution rather than a disruption [1] as production systems have a long lifecycle, invest- ment protection is required and engineers are frequently guided by the motto “Never change a running system.“ During the R&D efforts for our SmartFactory Web [2] (SFW), an industrial platform for smart factories, which is at the same time the official test bed of the Industrial Internet Consortium (IIC), IOSB engineers have come to the conclusion that these platforms can actually have disruptive effects on the man- ufacturing industry. SFW aims at improving the value chain by flexibly equalizing the capacities between the smart factories participating in the platform. To this end, the factories register with the SFW por- tal, allowing customers to find appropriate production capacities. By now, SFW even provides features to manage supply chains and networks. Since manufacturing enter- prises usually depend on suppliers and are distributed across several sites, this func- tionality is a major step towards achieving improvements and enabling negotiations across enterprises and organizations. Today, various manufacturing-as-a-service (MaaS-)platforms have established them- selves in the market, offering the production of parts as a service – usually still in the form of NC chip making, 3D printing or sheet metal production. Manufacturers can join these platforms by offering their resources and thus their production capacities; the platform carries out all management activities. On the basis of the 3D data provided by the customer, e.g. STEP-files, the software automatically calculates the price and the delivery date and assigns the manufacturing order to one of the participating factories. Thus, end customers do not have any direct contact with the man- ufacturer any more, they only access the plat- form. In addition, the platform manages the entire logistics and – should a manufacturer need to invest in capacity expansions – even the investment in these expansions. Owing to embedded AI, the platforms is able to learn from the geometries, including the improve- ment of the NC programs. In extreme cases, Image/Graphic: © IOSB Legend: Lifecycle-related data Configuration and asset data Activity Objects of the class order Objects of the class product Objects of the class resource Logistic/delivery data Deadlines Documentation Data on resource allocation planning Planning and control algorithms Customer enquiries, Part geometry, quantity, quality, tolerances, dead-, lines etc. MaaS platform, SFW, etc. Manufacturing orders Production, assembly Raw materials Deliverable parts Machine Commissioning Order-independent components, e.g. spindle, ball screw drive Order-independent components, e.g. tools, NC programs Material data Delivery data Asset models Asset models at instance level Asset models, information models Lifecycle/TCO data Operating/machine data acquisition ML models QA data energy data IDS IDS Connector IDS Connector IDS connector IDS Connector IDS Connector IDS Connector IDS Connector IDS Connector IDS Connector IDS Connector Overview of a potential application case (Terminology in accordance with https://de.wikipedia.org/wiki/Integrierte_Unternehmensmodellierung)