Litcius/Paper detail

Application of the Taguchi Method and Grey Relational Analysis for Multi-Objective Optimization of a Two-Stage Bevel Helical Gearbox

Tran Huu Danh, Lê Xuân Hưng, Nguyen Thi Thanh Nga, Xuan-Tu Hoang, Quy-Huy Trieu, Vu Ngoc Pi

2023Machines27 citationsDOIOpen Access PDF

Abstract

This paper introduces a novel approach to deal with the multi-objective optimization of a two-stage bevel helical gearbox by applying the Taguchi method and Grey Relation Analysis (GRA). The goal of the study is to find optimal main design factors that minimize the gearbox volume and maximize the gearbox efficiency. To accomplish this, five main design parameters were selected: the coefficients of wheel face width (CWFW) of the bevel and the helical gear sets, the allowable contact stresses (ACS) of the first and the second stages, and the gear ratio of the first stage. Furthermore, two single targets were investigated: minimum gearbox volumes, and maximum gearbox efficiency. Also, the multi-objective optimization problem is solved through two steps: Step 1 for closing the gap between variable levels and Step 2 for determining the optimal main design factors. The study’s findings were used to introduce the optimum values of five major design parameters for designing a two-stage helical gearbox.

Topics & Concepts

Taguchi methodsBevelBevel gearGrey relational analysisEngineeringVolume (thermodynamics)Optimal designComputer scienceMechanical engineeringMathematicsStatisticsMachine learningQuantum mechanicsPhysicsGear and Bearing Dynamics AnalysisMechanical Engineering and Vibrations ResearchManufacturing Process and Optimization