On the public citation graph

The study of machine learning for wire rupture prediction in WEDM

https://doi.org/10.1007/s00170-021-08323-5
0 signed · 32 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00170-006-0632-1openalex-snapshot
Finishing effect of abrasive flow machining on micro slit fabricated by wire-EDM
inferredcites →https://doi.org/10.1007/s00170-013-4995-9openalex-snapshot
Study on surface characteristics using phosphorous dielectric on wire electrical discharge machining of polycrystalline silicon
inferredcites →https://doi.org/10.1007/s00170-014-6243-3openalex-snapshot
Review of improvements in wire electrode properties for longer working time and utilization in wire EDM machining
inferredcites →https://doi.org/10.1007/s00170-020-06218-5openalex-snapshot
Optimization of WEDM for precise machining of novel developed Al6061-7.5% SiC squeeze-casted composite
inferredcites →https://doi.org/10.1007/s10845-008-0097-1openalex-snapshot
Estimation of cutting forces and surface roughness for hard turning using neural networks
inferredcites →https://doi.org/10.1016/j.ijmachtools.2004.04.017openalex-snapshot
State of the art in wire electrical discharge machining (WEDM)
inferredcites →https://doi.org/10.1016/j.jmatprotec.2008.07.023openalex-snapshot
Prediction and control of surface roughness in CNC lathe using artificial neural network
inferredcites →https://doi.org/10.1016/j.measurement.2016.06.048openalex-snapshot
Prediction of surface roughness in hard turning under high pressure coolant using Artificial Neural Network
inferredcites →https://doi.org/10.1016/j.procir.2021.03.109openalex-snapshot
Support vector machine regression for predicting dimensional features of die-sinking electrical discharge machined components
inferredcites →https://doi.org/10.1016/s0924-0136(00)00438-6openalex-snapshot
Optimization of the electrical discharge machining process based on the Taguchi method with fuzzy logics
inferredcites →https://doi.org/10.1016/s0924-0136(99)00107-7openalex-snapshot
Rupture failure and mechanical strength of the electrode wire used in wire EDM
inferredcites →https://doi.org/10.1051/matecconf/20179507014openalex-snapshot
Wire Rupture Optimization in Wire Electrical Discharge Machining using Taguchi Approach
inferredcites →https://doi.org/10.1080/10426914.2013.852203openalex-snapshot
Processing Characteristics Using Phosphorous Dielectric on Wire Electrical Discharge Machining of Polycrystalline Silicon
inferredcites →https://doi.org/10.1109/icufn.2016.7536995openalex-snapshot
Consideration of manufacturing data to apply machine learning methods for predictive manufacturing
inferredcites →https://doi.org/10.1109/tbme.2004.826679openalex-snapshot
Microelectrode Array Fabrication by Electrical Discharge Machining and Chemical Etching
inferredcites →https://doi.org/10.1142/8868openalex-snapshot
Principles of Artificial Neural Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4773674openalex-extracted
A Machine Learning Based Multi-Objective Optimization in Wedm of Nab Alloy
inferred← citeshttps://doi.org/10.1007/s00170-022-10240-0openalex-snapshot
Wire breakage prevention for reciprocated traveling WEDM based on discharge location detection
inferred← citeshttps://doi.org/10.1007/s00170-024-13631-7openalex-snapshot
Comparison of MRR of different WEDM-machined materials
inferred← citeshttps://doi.org/10.1007/s00170-025-15508-9openalex-snapshot
Enhanced multi-stage laser forming path prediction through transfer learning and imaginary data validation
inferred← citeshttps://doi.org/10.1007/s12008-023-01642-9openalex-snapshot
Wire-breakage prediction during WEDM of Ni-based superalloy using machine learning-based classifier approaches
inferred← citeshttps://doi.org/10.1007/s12008-024-01923-xopenalex-snapshot
Investigation and prediction of machining characteristics of aerospace material through WEDM process using machine learning
inferred← citeshttps://doi.org/10.1007/s13369-024-09526-0openalex-snapshot
Optimization of Kerf Width in WEDM of Sandwich Woven CFRP-An Ensemble Machine Learning Based Approach
inferred← citeshttps://doi.org/10.1007/s42452-025-07385-4openalex-snapshot
A state-of-the-art review of soft computing-based monitoring and control in the machining of hard alloys
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.115257openalex-snapshot
State of the art of the role of artificial intelligence in electrical discharge machining: A review
inferred← citeshttps://doi.org/10.1038/s41598-025-34151-8openalex-snapshot
Predictive modelling and optimization of WEDM of nickel aluminium bronze alloy using optimised support vector regression and evolutionary algorithm
inferred← citeshttps://doi.org/10.1155/2022/5192981openalex-snapshot
Examination of Machining Parameters and Prediction of Cutting Velocity and Surface Roughness Using RSM and ANN Using WEDM of Altemp HX
inferred← citeshttps://doi.org/10.1177/09544089261483338openalex-snapshot
Machine learning-assisted prediction and Bayesian optimisation of wire EDM process parameters for surface roughness of AISI S7 tool steel
inferred← citeshttps://doi.org/10.3390/app122412858openalex-snapshot
Research on the Tooth Surface Integrity of Non-Circular Gear WEDM Based on HPSO Optimization SVR
inferred← citeshttps://doi.org/10.3390/jmmp8050206openalex-snapshot
Optimizing High-Performance Predictive Modeling of the Medium-Speed WEDM Processing of Inconel 718
inferred← citeshttps://doi.org/10.3390/met15070706openalex-snapshot
Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining
inferred← citeshttps://doi.org/10.52209/2706-977x_2025_4_110openalex-snapshot
Minimizing Wire Breakage in Wire Electric Discharge Machining Using Multi-Objective Artificial Bee Colony Algorithm
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.