RETRACTED: Prediction of energy consumption of numerical control machine tools and analysis of key energy‐saving technologies
Abstract The objective of this study is to ensure the sustainable development of traditional machinery manufacturing industry under limited conditions of non‐renewable energy, and reduce the environmental pollution caused by high energy consumption of machine tools. Here the energy consumption of nu...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-09-01
|
| Series: | IET Collaborative Intelligent Manufacturing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cim2.12001 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract The objective of this study is to ensure the sustainable development of traditional machinery manufacturing industry under limited conditions of non‐renewable energy, and reduce the environmental pollution caused by high energy consumption of machine tools. Here the energy consumption of numerical control machine tools is analysed, and the relevant energy‐saving model is established. The energy consumption system of the numerical control machinery tools, including the cutting parameters, is classified. The relevant energy consumption prediction model is built to evaluate the influence of different cutting parameters, feed per tooth, and the back cutting depth on the energy consumption of numerical control machine tools. The results show that classifying the energy consumption system of numerical control machine tools can effectively predict the energy consumption of machine tools, which provides theoretical support for the subsequent energy‐saving experiments. Larger cutting parameters will increase the energy consumption of numerical control machine tools, improve the energy efficiency of machine tools at the same time. Thus, reducing the feed per tooth and the back cutting depth can effectively decrease its energy consumption. The results of this study provide data support and guidance for the energy‐saving experiments and practical applications of numerical control machine tools. |
|---|---|
| ISSN: | 2516-8398 |