Machining Process Optimization Using a Model Based on Criterial Functional Dependence
This research deals with the optimization of the machining process using a model based on criterial functional dependence hypothesis. The basis of this hypothesis is the assertion that for each production process of a given product with many input parameters, at given known requirements and conditio...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/13/6/478 |
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| Summary: | This research deals with the optimization of the machining process using a model based on criterial functional dependence hypothesis. The basis of this hypothesis is the assertion that for each production process of a given product with many input parameters, at given known requirements and conditions, it is possible to determine the minimum/maximum local extremum, that is, to find the most suitable conditions under which the criterion is achieved. To verify the optimization model, three different cutting tools (cutting inserts) were compared within the criteria functions set for cutting force <i>F<sub>c</sub></i>, process power <i>P</i>, and surface roughness characteristics <i>Rz</i>, all with two independent variables—cutting speed <i>v<sub>c</sub></i> and feed <i>f</i>. The technology of turning with longitudinal external machining of the cylindrical surface was selected as the operation for the experiment. Taking into account the importance of individual criteria for real practice and the minimum extreme values achieved (a surface roughness <i>Rz</i> = 2.2 μm and cutting power <i>p</i> = 14,700 W at <i>v<sub>c</sub></i> = 145 m/min and <i>f</i> = 0.8 mm), the tool with a linear cutting edge (LCE) designed at the authors’ workplace appeared as the most suitable tool for machining operation under the given conditions when compared with commercially produced cutting tools TCMT 16T308-PR 4035 and CNMG 120408-WM 4025. |
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| ISSN: | 2075-1702 |