Abstract

Dry cutting as an important sustainability manufacturing technology is enhancing ever-higher levels of hypoid gear production. To improve economic and environmental attributes of sustainability manufacturing, a new data-driven dry cutting tool collaborative optimization model considering both geometric accuracy and loaded contact performances is established for face-hobbing hypoid gears. Where, an innovative ease-off tooth contact analysis (e-TCA) method is proposed to establish accurate relations between ease-off flank and loaded contact performance evaluations. Then, for the initial design flank from arc-shaped tool, Top-Rem tool modification is applied to establish the collaborative optimization model. By fine-modifying the ease-off flank relating to Top-Rem tool parameters, the current design flank can get an adaptive approximation to the target flank requiring the loaded contact performance evaluations. Moreover, in addition to the accuracy and efficiency of dry cutting at its own, the cutting gear number of per hour, cutting gear number of per tool and cutting power consumption are used the main assessment items on sustainability. The numerical and experimental examples are provided to verify that the proposed tool collaborative optimization model will significantly improve sustainability in terms of economic and environmental assessments.

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