Abstract
The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted CAD/CAM (computer-aided design/computer-aided manufacturing) planning. Thereby, a laser-triangulation sensor is integrated into the machine tool. For an automatic raw-part detection and a workpiece origin definition, a dedicated algorithm for creating a digital blank shadow is introduced. The algorithm generates adaptive scan paths, merges laser lines and machine axis data, filters interference signals, and identifies part edges and surfaces according to a point cloud. Furthermore, a dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC (computer numerical control) machine. The results of this study show that the applied method can identify the positions, dimensions, and shapes of different raw parts autonomously, with deviations less than 1 mm, in 2.5 min. Moreover, the measurement and process data can be transferred without errors to different hardware and software systems. It was found that the proposed approach can be applied for rough raw-part detection, and in combination with a touch probe for accurate detection.
Highlights
Because of globalization and product individualization, the demand for product variability and highly dynamic product lifecycles will grow in future years [1]
This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted computer-aided design (CAD)/computer-aided manufacturing (CAM) planning
A dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC machine
Summary
Because of globalization and product individualization, the demand for product variability and highly dynamic product lifecycles will grow in future years [1]. The resulting point cloud is used for registration with the iterative closest point algorithm and for automatic object detection, which is based on two-dimensional template matching. These various examples show that laser scanning systems for raw-part detection can acquire high-precision data while accomplishing a short measuring time [12,17]. The accuracy is low compared to other technologies [20,21] Besides these two measuring principles, structured light methods are used to acquire digital workpiece representations [22,23]. The current approaches are mostly unable to automatically generate a digital shadow of the detected workpiece.
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