Semiconductor production represents one of the most complex manufacturing processes with more than 1000 steps solely within the front-end production and the complexity continues to increase. Semiconductors are manufactured in high-purity clean rooms. To manage joint production of power semiconductors and logic technologies in one fab, it is necessary to create guidelines enabling the parallel production of these two technologies without negatively influencing each other. Especially with the production of power semiconductors, various components such as noble metals and organic substances are involved. This requires a comprehensive strategy for maintaining the level of cleanliness in the manufacturing area. Novel automation mechanisms and algorithms will be applied to understand, control, and ultimately prevent the contamination of the products. Highly automated and digitalized processes already supply a large amount of data to various databases. A major challenge is collecting and storing the right data in real-time. Suitable software applications are also needed to process the data in a way that overcomes database and media disruptions. This enables the creation of safe cleanroom concepts. This article shows a way to overcome the challenges at one of the largest semiconductor sites in Europe for smart power technologies using advanced data analytics and machine learning approaches.