Evaluation of Machinability and Energy Consumption of CK45 Steel Using Synthetic-Based Nanofluid and Minimum Quantity Lubrication Cutting Fluid
CK45 steel has various industrial uses due to its durability, wear resistance and strength. It is generally used in machinery, automotive industry, hydraulic cylinders, bearings, gears and similar applications. It is important to investigate the machinability properties of CK45 steel, which is frequ...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Metals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4701/15/1/36 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | CK45 steel has various industrial uses due to its durability, wear resistance and strength. It is generally used in machinery, automotive industry, hydraulic cylinders, bearings, gears and similar applications. It is important to investigate the machinability properties of CK45 steel, which is frequently used in the manufacturing industry, in different cooling/lubrication environments. This study focused on the effects of a synthetic-based nanofluid cooling strategy and different cutting parameters during the milling of CK45 steel. Additionally, Taguchi analysis was performed to reduce the number of experiments and costs. Sustainable cooling/lubrication techniques were used during milling. A three-axis computer-controlled machine was used for the milling process. According to the findings, flank wear, surface roughness, and energy consumption were reduced by machining in the nanofluid environment. It was observed that Cu nanoparticles added into the nanofluid increased the machinability properties. Furthermore, statistical analysis was employed to ascertain the predominant control variables influencing the response parameters. Machinability efficiency can be increased by using nanoparticulate fluids as a coolant during milling. In addition, costs can be reduced by identifying the most effective factors in the experiment through statistical analysis. |
|---|---|
| ISSN: | 2075-4701 |