Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Instance-Based Learning Algorithms
Machine Learning
Data mining and knowledge discovery in databases
Communications of the ACM
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Learning in graphical models
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Feature subset selection by Bayesian network-based optimization
Artificial Intelligence
Principles of data mining
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Machine Learning and Data Mining; Methods and Applications
Machine Learning and Data Mining; Methods and Applications
Machine Learning
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Learning Bayesian Networks
On the use of Bayesian Networks to develop behaviours for mobile robots
Robotics and Autonomous Systems
A Bayesian network model for surface roughness prediction in the machining process
International Journal of Systems Science
Expert Systems with Applications: An International Journal
Bayesian classifiers based on kernel density estimation: Flexible classifiers
International Journal of Approximate Reasoning
Optimising Machine-Learning-Based Fault Prediction in Foundry Production
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Data Mining for Burr Detection (in the Drilling Process)
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
On biases in estimating multi-valued attributes
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A clustering approach for determining the optimal process parameters in cutting
Journal of Intelligent Manufacturing
Probabilistic graphical models in artificial intelligence
Applied Soft Computing
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One of the most important processes in the aeronautical sector is drilling. The main problem associated with drilling is burr. There is a tolerance level for this burr and it cannot exceed 127 microns, which would provoke structural damage and other problems. Currently, the burr elimination task is carried out visually and manually with the aim of guaranteeing quality in the process. However, it is an expensive procedure and needs to be replaced by a motorized system capable of automatically detecting in which holes the burr exceeds the permitted level and has to be eliminated or reduced. The paper presents a burr prediction model for high speed drilling in dry conditions on aluminium (Al 7075-T6), based on a Bayesian network learned from a set of experiments based on parameters taken from the internal signal of the machine and parameters from the condition process. The paper shows the efficiency and validity of the model in the prediction of the apparition of burr during the drilling and compares the results with other data-mining techniques.