## 1 Introduction  
Microdevices are crucial components in diverse, complex products that promise increasingly high growth in many different industries [1]. The most common mechanical microcomponents are microgears, which are used in a wide range of applications, e.g., in the fields of aerospace technology, medical technology, and robotics [2, 3]. Microgears have a particularly complex geometry and thus the manufacturing requirements often reach technological limits. In the case of dental instruments such as dental drills, the relatively large geometric deviations of microgears, in comparison to the small component size, have a major influence on the function as well as the generation of unwanted noises and vibrations, which have a direct influence on patients and treating physicians. The main cause is excitations generated during tooth meshing, which are transmitted by means of structure-borne vibrations and radiated as airborne sound. Gear deviations such as profile and flank deviations lead to less than ideal tooth meshing and must therefore be detected and avoided [4, 5]. Quality assurance by means of suitable measurement technologies is therefore very important in the context of microgear production.  
A comprehensive study by the Physikalisch-Technische Bundesanstalt (PTB) on the potentials and requirements of microgear measuring technology shows, that the quality of the achievable measurement results is not yet sufficient for the high, and in the future further increasing, demands placed on microgear manufacturers [6]. In addition to readily available measurement methods for measuring samples in a measuring room, 100% inline measurements would be necessary to enable control strategies in the sense of a closed-loop approach to further increase the efficiency of the manufacturing processes. The lack of accessibility due to complex geometric features is a major barrier to the use of tactile and optical measurement methods for comprehensive quality assurance of microgears. Furthermore, the long measurement time and the high costs for measuring machines capable of measuring in the single-digit micrometer range represent further barriers to economical 100% inline measurements.  
This paper examines the integration of an acoustic emission sensor into the manufacturing process of microgears in order to predict process parameters as well as geometric features. The developed method is investigated with a use case from the dental industry using the example of the gear hobbing process. Hobbing is the most commonly used process for the production of gears. It is a complex process with multidimensional intersections and simultaneous rotation of tools and workpieces. So far, hobbing has been investigated mainly in terms of tool wear. Both electrical current signals [4] as well as airborne sound [7] and structure-borne sound signals [8] are already being used successfully for this purpose. The use of machine learning and data analysis in combination with structure-borne sound signals has the potential to predict the quality of the produced gears. Furthermore, this approach would enable process control in the sense of a closed-loop approach to further increase the efficiency of the hobbing process.