Optimization of process parameters in turning operation using CNT based minimum quantity lubrication (MQL). (2023)
- Record Type:
- Journal Article
- Title:
- Optimization of process parameters in turning operation using CNT based minimum quantity lubrication (MQL). (2023)
- Main Title:
- Optimization of process parameters in turning operation using CNT based minimum quantity lubrication (MQL)
- Authors:
- Jagatheesan, K.
Babu, K.
Madhesh, D. - Abstract:
- Abstract: Smart and modern machining process is a key success parameter in process economics. Various machining methodologies have proven success in their respective verticals, but they possess certain limitations such as power loss, voluminous coolant, effective disposal of used coolants/oils, detrimental chip hazards to workers etc. earlier one factor at a time (OFAT) approach was implemented to overcome these limitations, but later these limitations were taken over by chemometric approaches such as Taguchi method, Response surface methodology (RSM) such as Central Composite Design (CCD) and Box-Benkhen design (BBD) and Doehlert's design. In our study, three process variables such as carbon nanotubes (CNT) concentration (%), pressure (bar) and flow rate (ml/hr) were selected and experiment was conducted based on 15 run Box-Benkhen design, to optimize the effect of CNT on minimum quantity lubrication towards its effectiveness on machining of EN24 Alloy steel. At desirability factor of 1, a projected cutting force response of 218.28 (kgf) was obtained using CNT concentration (0.79 mg/L), pressure (6 bar), and flow rate (158.586 ml/hr) (kgf). Likewise, with a desirability factor of 1, the optimal anticipated conditions giving CNT concentration (0.828 mg/L), pressure (6 bar), and flow rate (135.354 ml/hr) yielded a projected surface roughness response of 3.3969 (μm). The experimental values were determined to be 211.32 (kgf) and 3.362 (μm) at the predicted conditions. At theAbstract: Smart and modern machining process is a key success parameter in process economics. Various machining methodologies have proven success in their respective verticals, but they possess certain limitations such as power loss, voluminous coolant, effective disposal of used coolants/oils, detrimental chip hazards to workers etc. earlier one factor at a time (OFAT) approach was implemented to overcome these limitations, but later these limitations were taken over by chemometric approaches such as Taguchi method, Response surface methodology (RSM) such as Central Composite Design (CCD) and Box-Benkhen design (BBD) and Doehlert's design. In our study, three process variables such as carbon nanotubes (CNT) concentration (%), pressure (bar) and flow rate (ml/hr) were selected and experiment was conducted based on 15 run Box-Benkhen design, to optimize the effect of CNT on minimum quantity lubrication towards its effectiveness on machining of EN24 Alloy steel. At desirability factor of 1, a projected cutting force response of 218.28 (kgf) was obtained using CNT concentration (0.79 mg/L), pressure (6 bar), and flow rate (158.586 ml/hr) (kgf). Likewise, with a desirability factor of 1, the optimal anticipated conditions giving CNT concentration (0.828 mg/L), pressure (6 bar), and flow rate (135.354 ml/hr) yielded a projected surface roughness response of 3.3969 (μm). The experimental values were determined to be 211.32 (kgf) and 3.362 (μm) at the predicted conditions. At the expected ideal conditions, the experimental value was found to be quite close to the predicted value. … (more)
- Is Part Of:
- Materials today. Volume 72(2023)Part 4
- Journal:
- Materials today
- Issue:
- Volume 72(2023)Part 4
- Issue Display:
- Volume 72, Issue 4, Part 4 (2023)
- Year:
- 2023
- Volume:
- 72
- Issue:
- 4
- Part:
- 4
- Issue Sort Value:
- 2023-0072-0004-0004
- Page Start:
- 2552
- Page End:
- 2556
- Publication Date:
- 2023
- Subjects:
- EN 24 Alloy steel -- Turning -- Optimization -- Cutting force -- Surface Roughness -- Lubrication
Materials science -- Congresses -- Periodicals
620.1 - Journal URLs:
- http://www.sciencedirect.com/science/journal/22147853 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.matpr.2022.09.606 ↗
- Languages:
- English
- ISSNs:
- 2214-7853
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25046.xml