Abstract
Stainless steel has numerous applications in medical, engineering and industrial fields. It is recognized as difficult to machine (DTM) material. Conventional machining is challenging and also environmentally-unfriendly. Therefore, in the present work, SS304 has been attempted to machine using coated carbide tools under dry environment. This paper reports the investigation conducted on analysis of the effects of machining parameters such as cutting speed, feed rate, and depth of cut on productivity (material removal rate) and surface quality (average surface roughness); and optimization of machining parameters for the best values of these machinability indicators. Taguchi L9 orthogonal array based experimentation has been done. ANOVA has also been conducted to verify the statistical fitness and significant parameters. Grey relational technique has been used for optimization. Dry machining of SS304 at optimum combination of machining parameters i.e. cutting speed: 70m/min; feed: 0.1mm/rev; depth of cut: 1mm resulted in the optimized values of machinability indicators i.e. material removal rate-116.67 mm3/s and average surface roughness-1.99 μm.
| Original language | English |
|---|---|
| Pages (from-to) | 781-789 |
| Number of pages | 9 |
| Journal | Proceedings of the International Conference on Industrial Engineering and Operations Management |
| Issue number | July |
| Publication status | Published - 2019 |
| Event | 3rd Eu International Conference on Industrial Engineering and Operations Management,IEOM 2019 - Pilsen, Czech Republic Duration: 23 Jul 2019 → 26 Jul 2019 |
Keywords
- Dry machining
- Machinability
- Optimization
- Stainless steel
- Surface quality
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Control and Systems Engineering
- Industrial and Manufacturing Engineering