In traditional dough kneading machines the ingredients, e.g. flour, water, salt and yeast are filled into a cylindrical vessel and mixed by means of a rotating spiral. In order to assure consistent dough quality while environmental conditions and flour characteristics vary, an experienced baker needs to 1) manually set the rotational speed as well as the time for kneading and 2) continuously monitor the kneading process. The overall goal of this work is to develop an intelligent kneading machine that autonomously decides how to set the speed and when to stop kneading. This machine assists the bakers work and allows for more efficient use of kneaders as part of autonomous production systems. We describe the design of intelligent information processing algorithms that were implemented in a technology demonstrator and validated with the expertise of professional bakers. While focusing on the control software, the underlying concepts are explained and relevant results are shown. In particular, reliable detection of phase-shifts and model-based prediction of dough properties was achieved.