Solving a Multi-Objective Optimization Problem of a Two-Stage Helical Gearbox with Second-Stage Double Gear Sets Using the MAIRCA Method

• Published in: Applied sciences Vol. 14; no. 12; p. 5274
• Main Authors: Vu, Duc-Binh, Tran, Huu-Danh, Dinh, Van-Thanh, Vu, Duong, Vu, Ngoc-Pi, Nguyen, Van-Trang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2024
• Subjects: Adhesive wear; Bending stresses; Decision making; Design optimization; Efficiency; gear ratio; gearbox; Genetic algorithms; helical gearbox; MAIRCA method; Methods; multi-objective optimization; Objectives; Optimization techniques; Set design
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app14125274

This paper provides a novel application of the multi-criteria decision-making (MCDM) method to the multi-objective optimization problem (MOOP) of creating a two-stage helical gearbox (TSHG) with second-stage double gear sets (SDGSs). The aim of the study is to determine the optimum major design components for enhancing the gearbox efficiency while reducing the gearbox volume. In this work, three primary design parameters are chosen to accomplish this: the gear ratio of the first stage and the coefficients of the wheel face width (CWFW) of the first and second stages. Additionally, the study is conducted with two distinct objectives in mind: the lowest gearbox volume and the maximum gearbox efficiency. Moreover, phase 1 and phase 2, respectively, are the two stages of the MOOP. Phase 2 handles the MOOP to identify the ideal primary design factors as well as the single-objective optimization problem to minimize the difference between the variable levels. Additionally, the Multi-Attributive Ideal–Real Comparative Analysis (MAIRCA) approach is selected to deal with the MOOP. The results of the study are utilized to determine the ideal values for three crucial design parameters in order to create a TSHG with SDGSs.