In the era of digitalization, more and more production facilities are being modernized and networked, mostly driven by large industrial concerns. With Industry 4.0, fully networked smart factories are emerging, which results in a deconstruction of the classic automation pyramid through the use of Cyber Physical Production Systems (CPPS). The implementation of new digitalization technologies based on the fourth industrial revolution is mainly driven by large industrial companies due to the usually high initial investment costs and the required know-how. Low-Cost Intelligent Automation (LCIA) aims to benefit of these technologies on a smaller scale, which makes this concept interesting for small and medium-sized enterprises (SMEs) with fewer financial resources and specialized personnel. Regardless of the size of a company, the involvement of skilled personnel at shop-floor level is essential for a successful digital transformation, hence Human-Machine Interfaces (HMI) play a central role in this development. This thesis describes the implementation of such an HMI using the example of a rolling mill. A proof of concept for LCIA implementation is demonstrated by using the Open Source programming language Python for development and inexpensive but appropriate hardware components. The raw data generated by the existing CPPS is automatically processed and filtered to create high quality data sets. A graphical user interface (GUI) allows the user to monitor the time history of important process parameters. This enables the machine operator to visualize, assess and, if necessary, react to occurring abnormal values, systematic errors and set machine parameters for each test performed. For the implementation at the Chair of Metal Forming, possible concepts were compared and evaluated in the initial stage. The interface was realized by applying a touch screen, which is operated by a single board computer, integrated into the chair's internal network. This concept should subsequently support the long-term establishment of new digitalization technologies through effective and employee-centered visualization and highlight opportunities for efficient and effective digital transformation in SMEs.