Modeling and Multi-objective Optimization Method of Machine Tool Energy Consumption Considering Tool Wear
| Autor: | Min Zhang, Bo Li, Xitian Tian |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.product_category
Renewable Energy Sustainability and the Environment Computer science business.industry Mechanical Engineering Energy consumption Multi-objective optimization Industrial and Manufacturing Engineering Machine tool Machining Management of Technology and Innovation Surface roughness Numerical control General Materials Science Tool wear business Process engineering Efficient energy use |
| Zdroj: | International Journal of Precision Engineering and Manufacturing-Green Technology. 9:127-141 |
| ISSN: | 2198-0810 2288-6206 |
| DOI: | 10.1007/s40684-021-00320-z |
| Popis: | The natural energy crisis and the increasingly serious environmental problems have imposed all industries to reduce energy consumption. During milling process, selecting a correct cutting parameters can not only greatly improve production quality and processing efficiency, but also can reduce energy consumption, in addition, tool wear also has a great impact on them. Therefore, a milling power consumption model of CNC machine tools is established based on modern machining theory is established in this article, unlike traditional energy consumption models, our model takes full account of cutting conditions and tool wear. The surface roughness of parts is one of the important indicators to measure the machining quality of machine tools. Therefore, taking milling process as research object, a multi-objective cutting parameters optimization model that takes the machining surface roughness, material removal rate (MRR) and machining energy consumption as the optimization goals was established. Furthermore, an intelligent optimization algorithm was proposed based on improved Teaching–Learning-Based Optimization (TLBO) to solve the model under various limited milling conditions. Finally, comparing experimental results of optimized parameter and empirical parameters, it shows that goals of reducing energy consumption, improving productivity and machining quality can be achieved by optimizing cutting parameters. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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