Back to Search
Start Over
Application of a Multi-Criterion Decision-Making Method for Solving the Multi-Objective Optimization of a Two-Stage Helical Gearbox.
- Source :
- Machines; Jun2024, Vol. 12 Issue 6, p365, 17p
- Publication Year :
- 2024
-
Abstract
- This paper provides a novel application of a multi-criterion decision-making (MCDM) method to the multi-objective optimization problem of designing a two-stage helical gearbox. This study's goal is to identify the ideal primary design elements that increase gearbox efficiency while reducing the gearbox cross-section area. In this work, three primary design parameters were selected for investigation: the gear ratio of the first stage and the coefficients of wheel face width (CWFW) of the first and second stages. The multi-objective optimization problem was further split into two phases: phase 1 solved the single-objective optimization problem of minimizing the gap between the variable levels, and phase 2 solved the multi-objective optimization issue of identifying the ideal key design factors. Moreover, the multi-objective optimization problem was handled by the SAW method as an MCDM approach, and the weight criteria were computed using the entropy approach. This study's significant characteristics are as follows: First, a multi-objective optimization problem was successfully solved using the MCDM approach (SAW technique) for the first time. Second, the power losses in idle motion were investigated in this work in order to determine the efficiency of a two-stage helical gearbox. From this study's findings, the ideal values for three major design parameters can be determined for the design of a two-stage helical gearbox. [ABSTRACT FROM AUTHOR]
- Subjects :
- DECISION making
MULTIPLE criteria decision making
ENTROPY
GEARBOXES
SAWS
Subjects
Details
- Language :
- English
- ISSN :
- 20751702
- Volume :
- 12
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Machines
- Publication Type :
- Academic Journal
- Accession number :
- 178187207
- Full Text :
- https://doi.org/10.3390/machines12060365