Increasing productivity is a constant demand for the manufacturing industry. Low-carbon-steel is one of the most commonly used ferrous materials in the part manufacturing market. Improving productivity as well as making the process eco-friendly by implementing a dry machining condition is the essential goal of this study.
Built-up-edge (BUE) is often formed in the low-carbon-steel machining process, which, results in poor surface finish and short tool life. The high-speed-machining technique can be used to reduce the BUE formation and realize an increase in productivity. Cubic boron nitride (CBN) tools are most commonly used in hard turning and cast-iron machining at high cutting speeds. There are a limited number of studies regarding low-carbon-steel machining with CBN under a high-speed and with a dry machining condition. In this study, the investigation shows the preferable type of CBN tool and the wear mechanisms involved during finish turning operations of AISI 1018 under high speed and dry machining conditions.
Test results show that a low CBN content with a TiCN binder and smaller grain size offers the best tool life and surface integrity of the final part. Currently manufacturers use coated carbide tools with a recommended cutting speed of 200-300m/min with coolant to complete the finishing process for turning low carbon steel parts. In this study, by implementing CBN tools under the dry condition at 500 m/min cutting speed (speed was selected from the preliminary test performed using the uncoated CBN from 500 to 1200 m/min), the buildup edge formation has been reduced, tool life was measured to increase by 307% compared to the benchmark tool (Coated Carbide), and surface finish was measured in the range of 0.8-1.6μm Ra. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/24946 |
| Date | January 2019 |
| Creators | Zhang, Kan |
| Contributors | Veldhuis, Stephen, Mechanical and Manufacturing Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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