Optimizing Machining of Machine Tool Casting Bodies by Means of Optical Scanning

Abstract

The hereby presented study reports on the results of research funded by the NCBiR improvement grant. The goal of the undertaken experimental effort was to eliminate the laborious process of marking out from the technological procedure of cast machining. Marking out, even in highly automatized machining enterprises, is performed manually. It assesses casting accuracy, as well as denotes surpluses on machining surfaces. The precision of marking out is, therefore, dependent on individual performance of a given worker. Moreover, gauging casts of cylindrical (non-perpendicular) shape is highly problematic. Incorrect marking out generates quantifiable material (cast iron) and machining losses, as well as production interruptions. Herein, we present an innovative cast machining technology based on cast model scanning. Prior to machining, each body is scanned according to the technology guidelines. The subsequent comparison of the cast model and the model of the machined body affords geometrical accuracy assessment of the cast and the determination of optimal machining surpluses. The surplus verifying criteria include: machining volume minimization, tool working motions minimization, and idle tool motion minimization. Moreover, in special cases, high productive cutting (HPC) or high speed machining (HSM) optimization of cast technology, as well as elimination of superfluous procedures (e.g. milling of machining datum surfaces), are possible. The proposed comparative analysis of the aforementioned 3D models additionally affords acquisition of data for positioning (horizontal alignment) of the machined cast, e.g. the required length of technological supports. The hereby presented experimental results (obtained in an industrial setting) confirm the proposed elimination of the marking out process, thereby affording time reduction of preparatory procedures, initial assessment, and positioning of the cast for machining, as well as a decrease of machining volume by approx. 10 % (for the investigated casts). Experimental simulation results allowed us to estimate the machining volume minimization reaching up to 25 % (depending on the cast shape and the machining process specifications). Moreover, our investigation indicated a possibility of detection of casting flaws caused by insufficient surface brushing down. As the casts are painted post-brushing, the interfering sand mold remains are easily overlooked and often cause cutting-tool damage leading to costly production interruptions.