Digitalisation opens up a wide range of opportunities for manufacturing companies to improve their processes and products, with ever-increasing volumes of operating data from technical systems offering particularly high potential. How this data can be exploited to expand and modernise service portfolios and optimise product planning processes was the subject of two research projects conducted by the Advanced Systems Engineering research group at Paderborn University.
IMPRESS: From product manufacturer to smart service provider
Smart services are digital services that build on data derived from smart products and generate added value for the user through continuous data collection and analysis. They are independent market services that go hand in hand with new, innovative business models. The successful introduction of a smart service in a manufacturing company requires the complete transformation of the company to a smart service provider. How companies can best shape such a transformation was investigated in the research project IMPRESS (“Instruments for pattern-based planning of hybrid value creation and work for the provision of smart services”), co-ordinated and led by the Advanced Systems Engineering research group at the Heinz Nixdorf Institute (HNI). A framework of instruments, consisting of a variety of solution patterns, methods and tools, was developed to enable companies to plan and complete their transformation to a smart service provider, and thereby independently establish smart services in their organisation and on the market. “Solution patterns help make complex situations easier to understand. This gives companies, in particular SMEs, a concrete tool for implementing their smart service idea,” says Professor Roman Dumitrescu, a professor at Paderborn University’s Department of Computer Science and a director at the Fraunhofer Institute for Mechatronic Systems Design IEM. Based on the reference model developed, the strategic orientation of the desired smart service business forms the starting point for the company’s transformation, while the market service and smart service business model, as well as the intra- and inter-company value creation required for the transformation are defined on the basis of the relevant strategic requirements.
The research project was funded by the German Federal Ministry of Education and Research (BMBF) and European Social Fund (ESF) until July this year, with around �3.2 million. The research partners, including the Heinz Nixdorf Institute, Fraunhofer IEM and Chemnitz University of Technology, developed the pattern-based instruments in co-operation with the enablers Weidmüller, FIWARE and Diebold Nixdorf. The user companies ISTOS, FREUND and MSF-Vathauer have successfully utilised the solution patterns developed to complete their transformation to a smart service provider. The instruments provide companies with an excellent means with which to systematically plan and implement their smart service transformation. The specially developed web application www.smartservice-transformation.com)provides public access to the instruments.
DizRuPt: DizRuPt: Data-driven planning of future product generations based on the analysis of use phase data
Whether smartphones, household appliances or industrial machines: Modern products are increasingly networked and collect extensive data during their use phase. For manufacturers of such products, this data can provide valuable insights, and consequently promising ideas for product improvements. How such data-driven product improvements can be achieved was the focus of the DizRuPt project (“Data-driven retrofit and product generation planning in mechanical and plant engineering”), which was also co-ordinated by the Advanced Systems Engineering research group at the Heinz Nixdorf Institute and completed in June. The solutions developed in this project enable companies to independently analyse the use phase data derived from their products and to exploit the results in their strategic product planning in a targeted manner. This allows them to identify sources of errors or user behaviour patterns, for example, which then constitute the starting point for the data-driven improvement of future product generations. According to Dumitrescu, this brings a wealth of benefits: “Conventional product planning is largely based on small and predominantly qualitative amounts of data, as well as subjective assessments by individuals. The systematic analysis of use phase data in product planning generates reliable insights into the use of products, which feed into more objective planning for future product generations. Products can therefore be planned in a way that is more compatible with their actual operation and use.” The main results of the project are the design of a comprehensive reference process and provision of integrated software support. A multitude of methodical steps within the reference process are also supported with transformation knowledge.
The DizRuPt project was also funded by the BMBF for a period of three years, to the tune of around �2.3 million. In addition to Paderborn University, which was the consortium leader, the Berlin Institute of Technology and South Westphalia University of Applied Sciences were also involved in the project as research partners. CONTACT Software was responsible for providing the project with software support. The research results were successfully tested and validated in four pilot projects with the user companies LASCO Umformtechnik, Weidmüller Interface, Diebold Nixdorf and Westaflex.
