A geometric error budget method to improve machining accuracy reliability of multi-axis machine tools
Published 2016 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A geometric error budget method to improve machining accuracy reliability of multi-axis machine tools
Authors
Keywords
Thermal errors, Tool wear, A comprehensive error model, Machining accuracy reliability, Geometric error budget
Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2016-09-20
DOI
10.1007/s10845-016-1260-8
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Tool wear monitoring based on kernel principal component analysis and v-support vector regression
- (2016) Dongdong Kong et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- An approach to optimize the machining accuracy retainability of multi-axis NC machine tool based on robust design
- (2016) Ligang Cai et al. PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
- A geometric accuracy design method of multi-axis NC machine tool for improving machining accuracy reliability
- (2015) Ligang Cai et al. Eksploatacja i Niezawodnosc-Maintenance and Reliability
- Accuracy enhancement of five-axis machine tool based on differential motion matrix: Geometric error modeling, identification and compensation
- (2015) Guoqiang Fu et al. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
- Machining accuracy reliability analysis of multi-axis machine tool based on Monte Carlo simulation
- (2015) Qiang Cheng et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Stiffness design of machine tool structures by a biologically inspired topology optimization method
- (2014) Baotong Li et al. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
- A metaheuristic for fast machining error compensation
- (2014) Roman Stryczek JOURNAL OF INTELLIGENT MANUFACTURING
- Thermal sensor selection for the thermal error modeling of machine tool based on the fuzzy clustering method
- (2013) Haitong Wang et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Tool path generation for algebraically parameterized surface
- (2013) Subhajit Sarkar et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Prediction of tool deflection and tool path compensation in ball-end milling
- (2013) Nasreddine Zeroudi et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Machine tool thermal error modeling and prediction by grey neural network
- (2011) Yi Zhang et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- On performance enhancement of parallel kinematic machine
- (2011) Dan Zhang et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Prediction of machining accuracy degradation of machine tools
- (2011) Kuang-Chao Fan et al. PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
- Application of ACO-BPN to thermal error modeling of NC machine tool
- (2010) Qianjian Guo et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- A methodology for systematic geometric error compensation in five-axis machine tools
- (2010) Abdul Wahid Khan et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- An approach for reliability-based robust design optimisation of angle-ply composites
- (2009) Carlos Conceição António et al. COMPOSITE STRUCTURES
- The modeling of mode choices of intercity freight transportation with the artificial neural networks and adaptive neuro-fuzzy inference system
- (2008) Ahmet Tortum et al. EXPERT SYSTEMS WITH APPLICATIONS
- Application of synthetic grey correlation theory on thermal point optimization for machine tool thermal error compensation
- (2008) J. Y. Yan et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started