Lightweight Design Method for Micromanufacturing Systems Based on Multi-Objective Optimization
This study proposes a multi-stage collaborative design framework integrating sensitivity analysis, response surface methodology (RSM), and topology optimization for synergistic lightweighting and performance enhancement of micromanufacturing systems using ultra-precision computer numerical control (CNC) machine tools. Overall sensitivity analysis identified the base and column as stiffness-critical components, while the spindle box exhibited significant weight-reduction potential. Using spindle box wall and bottom thickness as variables, RSM models for mass and stress were constructed. Multi-objective optimization via a genetic clustering algorithm achieved a 57.2% (590 kg) weight reduction under stress constraints (<45 MPa). Subsequent variable-density topology optimization (SIMP model) reconfigured the rib layouts of the base and column under volume constraints, reducing their weights by 38.5% (2844 kg) and 41.5% (1292 kg), respectively. Whole-machine validation showed that maximum static deformation decreased from 0.17 mm to 0.09 mm, maximum stress reduced from 58 MPa to 35 MPa, and first-order natural frequency increased from 50.68 Hz to 84.08 Hz, significantly enhancing dynamic stiffness. Cumulative weight reduction exceeded 3000 kg, achieving a balance between lightweighting and static/dynamic performance improvement. This work provides an effective engineering pathway for a structural design of high-end micromanufacturing systems.
Authors
- Seyed Hamed Hashemi Sohi (ORCID: https://orcid.org/0000-0002-8973-294X)
- Shan Li (ORCID: https://orcid.org/0000-0003-3609-7011)
Institutions
- Mapúa University (PH)
- Zhengzhou University (CN)
- Zhengzhou University of Science and Technology (CN)
- Zhengzhou Business University (CN)
Publication Details
- Journal
- Micromachines
- Published
- 2025-09-09
- DOI
- https://doi.org/10.3390/mi16091032
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00