With the availability of affordable depth-camera-systems like the Microsoft Kinect, Depth Imaging has seen a fast-growing number of applications in many different fields over the last years. Such systems can however be based on different measurement principles with widely differing parameters and hence are difficult to evaluate against a single benchmark. While accuracy and precision of depth-camera-systems inherently vary significantly with measuring distance and changing environments, and therefore impose heavy constraints on real world applications, they even allow for automated quality assurance in controlled environments. Context aware assistive systems in manual assembly environments push these boundaries by employing quality assurance in more open environments, where distracting influences by the worker or the work-space environment cannot be ruled out. The thesis concerns itself with the exploration and evaluation of different depth measuring approaches (e.g. Time of Flight, Structured Light, Stereo Vision) for usage in semi-controlled assembly environments. The still underexplored effects of material properties on measurements are experimentally evaluated and the resulting limitations of each approach for usage in assembly environments are discussed.