On the Machining of Involute Helical Gears - Prediction models on tool geometry, cut gear tooth surface topography, chip geometry, and tool cutting forces
Abstract: The modern requirements on power transmissions focus on energy efficiency, low noise and dynamic vibrations, and power density. In order to meet these requirements, the gear wheels must be manufactured to very high precision. Additionally, it should be economical to manufacture these gears within the tight requested tolerances. Gears manufactured within automotive, truck, and construction equipment are usually cut using milling tools. The profile accuracy and the surface roughness achieved after manufacturing, which determines the gear quality, are connected to the process parameters and possible manufacturing related errors. Prediction models to accurately determine gear quality, where tool and process related errors are taken into account, are needed in order to improve the manufacturing process. Tool life has also a strong economic impact in machining operations. Tool life prediction is an important part in optimization of the machining processes, where tool life is strongly connected the cutting forces and the geometry of the cut chips. In this work mathematical models are established in parametric form, based on analytical differential description. These models are developed in order to increase knowledge and understanding of the complex machining processes involved in gear manufacturing. Focus is on the cut gear tooth surface quality, and on milling related topics, such as cut chip geometry, tool cutting forces, and tool wear prediction. The mathematical models are used in a number of experimental studies presented in this thesis. The experimental studies were performed in industrial conditions, where tool and process related errors that are common in industrial applications have been considered. The correlation is very good, which shows the industrial applicability of the presented models.
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