2026-10-13T05:15:09Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33971266 2026-09-23T05:55:19Z category_91 portal_316 item_type_3 month_year_09_2026

Data Sheet 1_Development of an empirical regression model for predicting worm gear efficiency.pdf Rahul Honkalas (25094641) Bhagyesh Deshmukh (25094644) Prabhakar Pawar (25094647) Imran Chandarki (25094650) Sachin Salunkhe (18385161) Lenka Cepova (20410307) Mechanical Engineering design of experiments efficiency improvement module regression analysis worm gear worm wheel teeth <p>Worm gearboxes are widely used in industrial applications requiring high torque transmission and large speed reduction; however, their efficiency is strongly influenced by sliding friction, lubrication, heat generation and geometry. This study develops a constrained empirical modelling and optimisation methodology for an industrial single-start worm gearbox used in a continuous-duty soot-blower application. The input speed (342 rpm), centre distance and operating requirements are fixed, while the worm module and worm-wheel tooth count are varied over a manufacturable design space. Thirty-five design combinations are evaluated analytically, followed by local regression modelling and multi-criteria selection. To avoid kinematic redundancy, the revised regression uses module and worm-wheel tooth count as predictors because output speed is deterministically related to tooth count under fixed input speed. The selected configuration, m = 2.75 mm and Z₂ = 43, gives a calculated efficiency of 74.6%, compared with 68.8% for the existing m = 2.54 mm, Z₂ = 45 design. This corresponds to an absolute gain of 5.8 percentage points and a relative improvement of 8.43%, corresponding to approximately to 8.45%. The revised local regression gives R² = 0.9950, RMSE = 0.520 percentage points and MAPE = 0.574% within the investigated design domain. The methodology is intended as a transparent design-screening tool; experimental validation under controlled temperature, lubricant, surface and dynamic conditions remains necessary before production implementation.</p> 2026-09-23T05:55:19Z Dataset Dataset 10.3389/fmech.2026.1973503.s001 https://figshare.com/articles/dataset/Data_Sheet_1_Development_of_an_empirical_regression_model_for_predicting_worm_gear_efficiency_pdf/33971266 CC BY 4.0