An automated approach for machining allowance evaluation of casting parts
The inconsistency of casting parts is a major issue for subsequent automated machining processes. The lack of reasonable machining allowance analysis methods results in low automation level of finish machining process though higher accuracy sensors are well applied in 3D scanning of cast parts. Traditional analysis methods based on nonlinear optimisation are only suitable for sparse point data obtained by CMM (Coordinate-Measuring Machine). As the development of scanners and 3D point cloud registration technology, new methods are applied to machining allowance analysis, but those still fail to face the conditions, such as uncertain datum, casting defect and allowance adjustment. In this paper, an automated approach based on point cloud registration to machining allowance evaluation is presented. Three constraints – envelopment, localisation datum and evenly distributed allowance – are concerned for uncertain conditions of casting parts. Two stages, initial alignment and machining allowance optimisation, are detailed in implementation. This approach is validated to be practical and effective via two created models and several real casting parts.
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Document Type: Research Article
Affiliations: State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China
Publication date: November 2, 2019