Research on Precision Machining of CNC Machine Tools Based on Industrial Big Data Algorithms

Quality and efficiency are eternal themes of intelligent manufacturing, and the key equipment that affects quality and efficiency in metal cutting intelligent manufacturing production lines is CNC machine tools. CNC machine tools belong to precision manufacturing equipment. Although their technical indicators can reach a high level when leaving the factory, their machining accuracy is affected by factors such as fixtures, cutting tools, environmental temperature, vibration, component aging, and workpiece material consistency when applied to actual production lines. Therefore, this article introduces industrial big data algorithms to fully explore and showcase the value contained in industrial big data, effectively forming data-driven, fast iterative, and continuously optimized industrial intelligent systems, thereby effectively solving the problem of machining accuracy stability in intelligent manufacturing systems. The experimental results showed that all 30 workpieces were qualified after processing.

Authors

Publication Details

Published
2024-09-13
DOI
https://doi.org/10.1109/itme63426.2024.00029
Primary Topic
Engineering Technology and Methodologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Precision Machining of CNC Machine Tools Based on Industrial Big Data Algorithms

L. Z. Zhu, Jing Liu, Jun Guo, Yang Liu
Engineering Technology and Methodologies
article

Research on Precision Machining of CNC Machine Tools Based on Industrial Big Data Algorithms

L. Z. Zhu, Jing Liu, Jun Guo, Yang Liu
article en

Abstract

Quality and efficiency are eternal themes of intelligent manufacturing, and the key equipment that affects quality and efficiency in metal cutting intelligent manufacturing production lines is CNC machine tools. CNC machine tools belong to precision manufacturing equipment. Although their technical indicators can reach a high level when leaving the factory, their machining accuracy is affected by factors such as fixtures, cutting tools, environmental temperature, vibration, component aging, and workpiece material consistency when applied to actual production lines. Therefore, this article introduces industrial big data algorithms to fully explore and showcase the value contained in industrial big data, effectively forming data-driven, fast iterative, and continuously optimized industrial intelligent systems, thereby effectively solving the problem of machining accuracy stability in intelligent manufacturing systems. The experimental results showed that all 30 workpieces were qualified after processing.

Industry, innovation and infrastructure
Openalex Percentile: Top 58%
Engineering Technology and Methodologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.