Small and medium-sized enterprises (SMEs) in particular are experiencing challenges in the current crises due to fluctuating demand, short planning horizons and increasing technological advances by large companies with regard to trend topics such as digitization and CO2-neutral production. At the same time, there is high price pressure with growing customer expectations of the product-service bundle. In this context, R&D activities are of central importance in order to be able to offer customers the most unique benefits possible through the combination of innovative products and services. Offering data-based functions and services can make the difference here compared to competitors.
The objective of the project is to process data along the data value chain of the machine tool. In the process, the data passes through various stages from generation and acquisition to the provision of information for business decisions, thus increasing its value. The business model to be developed enables each participant to use data or information at any point in the value chain. At the same time, users and data providers retain full cost control. Various technologies are used for the implementation, such as a subscription solution or billing according to runtime or data volume. The revenue and cost model aims at a clear, quantifiable financial benefit for all stakeholders.
In the course of the project, the specific needs of the companies are first investigated. Subsequently, functional proof at the system level will be provided and validated for the digital product of the sensory motor spindle, including the business models and associated digital services. For the next step of implementing the digital product in customer applications, interoperability, data security and reliability in particular are essential, as existing functions must not be negatively affected during operation. With the successful implementation and validation, the system is to be transferred to other machines in order to scale the digital product.
This project is funded by the Hessian State Chancellery – Minister for Digital Strategy and Development. We thank for the opportunity to work on this project.