Al-Mg-MoS2 reinforced hybrid metal matrix: Bio-machinability characteristics
This study examines the biomachinability of Al–Mg–MoS₂ hybrid metal matrix composites (MMCs) produced using powder metallurgy (PM) in detail. This study is to utilize a specialized microbe, Thiobacillus Novellus, to machine Al-Mg-MoS₂. For biomachining, the required number of samples is prepared through a PM process with different composite formulations, including Al (90 %), Mg (5–7 %), and MoS₂ (3–5 %). To perform biomachining studies, the following bioprocess parameters are considered (shaking speed, pH, and temperature). The experimental design utilized an orthogonal array. The findings indicated that shaking speed, pH, and temperature had a significant impact on microbial machining efficiency. Sample 3 (Al–Mg–MoS₂: 90–5–5) demonstrated a balanced performance in terms of achieving better Surface Roughness (Ra) and Specific Materail Removal Rate (SMRR) compared to Samples 1 and 2. The MOGWO and Fuzzy MOGWO methods were utilized to prioritize the optimal process parameters. The approach determined the optimal parameters of 80 rpm, pH 2.5, and 35 °C, utilizing Sample 3 (Al–Mg–MoS₂: 90–5–5), which yielded a predicted Ra of 1.5708 µm and SMRR of 1.2795 mg/hr·cm², with an error margin of <1.5 %. This study is the first of its kind to use a fuzzy multi-objective Grey Wolf Optimization framework to optimize Ra and SMRR simultaneously, and it is also the first to apply biomachining to Al-Mg-MoS₂ hybrid metal matrix composites using Thiobacillus novellus . Research in biomachining has come a long way with this integrated microstructure-biological-optimization method.
Authors
- Belete Sirahbizu
- Thivyaa Ramesh (ORCID: https://orcid.org/0009-0009-9257-9630)
- S. Rajesh
- Narmada Ch
- K Jeyaprakash
Institutions
- Addis Ababa Science and Technology University (ET)
- Addis Ababa University (ET)
- Kalasalingam Academy of Research and Education (IN)
Publication Details
- Journal
- Scientific African
- Published
- 2025-12-10
- DOI
- https://doi.org/10.1016/j.sciaf.2025.e03131
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00