Force Prediction and Cutting-Parameter Optimization in Micro-Milling Al7075-T6 Based on Response Surface Method
Current Language EN
English English Türkçe Türkçe Español Español Português Português Pусский Pусский Filipino Filipino Tiếng Việt Tiếng Việt हिन्दी हिन्दी العربية العربية বাংলা বাংলা Deutsch Deutsch 中文 中文

Force Prediction and Cutting-Parameter Optimization in Micro-Milling Al7075-T6 Based on Response Surface Method

Zhou M;Chen Y;Zhang G;;
micromachines 2020 Vol. 11 pp. -
149
m2020micromachinesforce

Abstract

Optimization of cutting parameters in micro-milling is an important measure to improve surface quality and machining efficiency of the workpiece. Investigation of micro-milling forces prediction plays a positive role in improving machining capacity. To predict micro-milling forces and optimize micro …

Keywords

National Center for Biotechnology Information NCBI NLM MEDLINE pubmed abstract nih national institutes of health national library of medicine pmid:32796514 doi:10.3390/mi11080766 menghua zhou yinghua chen guoqing zhang

Access

URL:
https://www.pubmed.gov/32796514/

Citation

ID: 113774
Ref Key: m2020micromachinesforce
Use this key to autocite in SciMatic or Thesis Manager

References

References

No Bibliography

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
113774
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet
Gas fees required in SCI Coins
Buy SCI

Saymatik Web3.0 Wallet

Google Play
App Store