Hidden Markov models for state recognition in injection molding processes using acceleration data

This thesis first gives a detailed introduction to the topic of HMMs and examines the related issues in detail. Afterwards the concept of HMMs is applied to a practical application in the injection molding industry. A 3D accelerometer attached to the injection molding machine provides data of an injection molding process, which can be displayed in time series. The aim of this thesis is to use HMMs to identify the states of injection molding processes from 15 different data sets based on their acceleration data.