Multi-Objective Optimization of a Two-Stage Helical Gearbox with Second Stage Double Gear-Sets Using TOPSIS Method

The multi-criteria decision-making (MCDM) method was applied in a novel way in this study to the multi-objective optimization problem (MOOP) of designing a two-stage helical gearbox with double gear-sets in the second stage. Finding the best fundamental components to increase gearbox efficiency and...

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Bibliographic Details
Published in:Processes 2024-06, Vol.12 (6), p.1160
Main Authors: Van-Thanh, Dinh, Tran, Huu-Danh, Bui, Thanh-Danh, Vu, Duc-Binh, Duong Vu, Ngoc-Pi Vu, Thi-Thu-Huong Truong
Format: Article
Language:English
Subjects:
Bending stresses
Decision making
Design factors
Design optimization
Efficiency
Gear ratios
Gearboxes
Genetic algorithms
Geometry
Helical gears
Lubricants & lubrication
Methods
Multiple criterion
Multiple objective analysis
Objectives
Optimization
Pareto optimum
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Summary:The multi-criteria decision-making (MCDM) method was applied in a novel way in this study to the multi-objective optimization problem (MOOP) of designing a two-stage helical gearbox with double gear-sets in the second stage. Finding the best fundamental components to increase gearbox efficiency and decrease gearbox cross-section area was the aim of this study. Three main design factors were chosen for investigation in this work: the first stage gear ratio and the first and second stage coefficients of wheel face width (CWFW). Phase 1 solves the single-objective optimization problem to reduce the gap between variable levels, and phase 2 solves the MOOP to determine the optimal critical design factors. This additionally splits the MOOP into two phases. Additionally, the TOPSIS method was used as an MCDM approach to address the multi-objective optimization issue, and the entropy approach was used to compute the weight criteria. In this study, gearbox efficiency is calculated by considering power losses during idle motion. The multi-objective optimization of a helical gearbox with second stage double gear-sets is addressed using the TOPSIS technique for the first time.
ISSN:2227-9717
DOI:10.3390/pr12061160