数控制造机床源能量优化设计

IF 1 Q4 ENGINEERING, MECHANICAL
Ly Duc Minh, Nguyen Quang Sang, Petr Bilik, Radek Martinek
{"title":"数控制造机床源能量优化设计","authors":"Ly Duc Minh, Nguyen Quang Sang, Petr Bilik, Radek Martinek","doi":"10.15282/ijame.20.1.2023.12.0797","DOIUrl":null,"url":null,"abstract":"The quality of the power supplied to the machining center is a key factor in determining the accuracy of the machine’s operation. The precision of the machining center is to ensure that the spindle accuracy is less than 3 microns. This study proposes a digital numerical control system to control the quality of the power supply and control the accuracy of the spindle axis of the machining center to monitor the measurement results in real time. The computer vision system is set up according to the artificial intelligent (AI) technique to recognize human face objects and control the position of the processor respectively on each line. The online measurement system follows the digital numerical control (DNC) system applied at each processing line, measuring product dimensions, measuring conditions for setting up machining tools, and measuring machine coordinates. The system operates fully automatically, eliminating dependence on operator skill, and facilitating operation in control of machining conditions. Improve machining center operator satisfaction. After implementation of the improvement options, total cost down 1.740 USD per year, the monthly repair cost due to broken drill, spindle alignment decreased from $5000 to $3,300 per month. The scrap rate related to the hole size decreased from 0.47% to 0.23% (cost down $35 per month). Downtime for repair reduced from 20 hours per month to 7.5 hours per month (cost down $10 per month). Broken drill rate was reduced from 0.20% to 0.06% (cost down $100 per month).","PeriodicalId":13935,"journal":{"name":"International Journal of Automotive and Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimized Design of Source Energy for Manufacturing Machine by Digital Numerical Control\",\"authors\":\"Ly Duc Minh, Nguyen Quang Sang, Petr Bilik, Radek Martinek\",\"doi\":\"10.15282/ijame.20.1.2023.12.0797\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The quality of the power supplied to the machining center is a key factor in determining the accuracy of the machine’s operation. The precision of the machining center is to ensure that the spindle accuracy is less than 3 microns. This study proposes a digital numerical control system to control the quality of the power supply and control the accuracy of the spindle axis of the machining center to monitor the measurement results in real time. The computer vision system is set up according to the artificial intelligent (AI) technique to recognize human face objects and control the position of the processor respectively on each line. The online measurement system follows the digital numerical control (DNC) system applied at each processing line, measuring product dimensions, measuring conditions for setting up machining tools, and measuring machine coordinates. The system operates fully automatically, eliminating dependence on operator skill, and facilitating operation in control of machining conditions. Improve machining center operator satisfaction. After implementation of the improvement options, total cost down 1.740 USD per year, the monthly repair cost due to broken drill, spindle alignment decreased from $5000 to $3,300 per month. The scrap rate related to the hole size decreased from 0.47% to 0.23% (cost down $35 per month). Downtime for repair reduced from 20 hours per month to 7.5 hours per month (cost down $10 per month). Broken drill rate was reduced from 0.20% to 0.06% (cost down $100 per month).\",\"PeriodicalId\":13935,\"journal\":{\"name\":\"International Journal of Automotive and Mechanical Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Automotive and Mechanical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15282/ijame.20.1.2023.12.0797\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Automotive and Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15282/ijame.20.1.2023.12.0797","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 2

摘要

加工中心供电的质量是决定加工中心工作精度的关键因素。加工中心的精度是保证主轴精度小于3微米。本研究提出了一种控制电源质量和控制加工中心主轴精度的数字数控系统,对测量结果进行实时监控。计算机视觉系统是根据人工智能(AI)技术建立的,用于识别人脸物体和控制处理器在每条线上的位置。在线测量系统遵循应用于每条加工线上的数字数控(DNC)系统,测量产品尺寸、设置机床的测量条件和测量机坐标。该系统完全自动运行,消除了对操作人员技能的依赖,便于操作控制加工条件。提高加工中心操作人员的满意度。实施改进方案后,总成本每年下降1740美元,每月因钻头、主轴对中损坏而产生的维修费用从每月5000美元下降到3300美元。与孔尺寸相关的废品率从0.47%降至0.23%(每月成本降低35美元)。维修停机时间从每月20小时减少到每月7.5小时(每月成本降低10美元)。钻头破损率从0.20%降至0.06%(每月成本降低100美元)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimized Design of Source Energy for Manufacturing Machine by Digital Numerical Control
The quality of the power supplied to the machining center is a key factor in determining the accuracy of the machine’s operation. The precision of the machining center is to ensure that the spindle accuracy is less than 3 microns. This study proposes a digital numerical control system to control the quality of the power supply and control the accuracy of the spindle axis of the machining center to monitor the measurement results in real time. The computer vision system is set up according to the artificial intelligent (AI) technique to recognize human face objects and control the position of the processor respectively on each line. The online measurement system follows the digital numerical control (DNC) system applied at each processing line, measuring product dimensions, measuring conditions for setting up machining tools, and measuring machine coordinates. The system operates fully automatically, eliminating dependence on operator skill, and facilitating operation in control of machining conditions. Improve machining center operator satisfaction. After implementation of the improvement options, total cost down 1.740 USD per year, the monthly repair cost due to broken drill, spindle alignment decreased from $5000 to $3,300 per month. The scrap rate related to the hole size decreased from 0.47% to 0.23% (cost down $35 per month). Downtime for repair reduced from 20 hours per month to 7.5 hours per month (cost down $10 per month). Broken drill rate was reduced from 0.20% to 0.06% (cost down $100 per month).
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
2.40
自引率
10.00%
发文量
43
审稿时长
20 weeks
期刊介绍: The IJAME provides the forum for high-quality research communications and addresses all aspects of original experimental information based on theory and their applications. This journal welcomes all contributions from those who wish to report on new developments in automotive and mechanical engineering fields within the following scopes. -Engine/Emission Technology Automobile Body and Safety- Vehicle Dynamics- Automotive Electronics- Alternative Energy- Energy Conversion- Fuels and Lubricants - Combustion and Reacting Flows- New and Renewable Energy Technologies- Automotive Electrical Systems- Automotive Materials- Automotive Transmission- Automotive Pollution and Control- Vehicle Maintenance- Intelligent Vehicle/Transportation Systems- Fuel Cell, Hybrid, Electrical Vehicle and Other Fields of Automotive Engineering- Engineering Management /TQM- Heat and Mass Transfer- Fluid and Thermal Engineering- CAE/FEA/CAD/CFD- Engineering Mechanics- Modeling and Simulation- Metallurgy/ Materials Engineering- Applied Mechanics- Thermodynamics- Agricultural Machinery and Equipment- Mechatronics- Automatic Control- Multidisciplinary design and optimization - Fluid Mechanics and Dynamics- Thermal-Fluids Machinery- Experimental and Computational Mechanics - Measurement and Instrumentation- HVAC- Manufacturing Systems- Materials Processing- Noise and Vibration- Composite and Polymer Materials- Biomechanical Engineering- Fatigue and Fracture Mechanics- Machine Components design- Gas Turbine- Power Plant Engineering- Artificial Intelligent/Neural Network- Robotic Systems- Solar Energy- Powder Metallurgy and Metal Ceramics- Discrete Systems- Non-linear Analysis- Structural Analysis- Tribology- Engineering Materials- Mechanical Systems and Technology- Pneumatic and Hydraulic Systems - Failure Analysis- Any other related topics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信