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International Journal of Systems Science Volume 39, 2008 - Issue 12
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Original Articles

A Bayesian network model for surface roughness prediction in the machining process

M. Correa Departamento de Informática Industrial, Instituto de Automática Industrial, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, SpainCorrespondence[email protected]
,
C. Bielza Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain
,
M. de J. Ramirez Departamento de Mecatrónica y Automatización, Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM), Monterrey, Mexico
&
J.R. Alique Departamento de Informática Industrial, Instituto de Automática Industrial, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain
Pages 1181-1192 | Received 19 Apr 2007, Accepted 01 Nov 2007, Published online: 05 Nov 2008

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Hao Yan, Nurettin Dorukhan Sergin, William A. Brenneman, Stephen Joseph Lange & Shan Ba. (2021) Deep multistage multi-task learning for quality prediction of multistage manufacturing systems. Journal of Quality Technology 53:5, pages 526-544.
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Articles from other publishers (36)

Deniz Demircioglu Diren, Neslihan Ozsoy, Murat Ozsoy & Huseyin Pehlivan. (2023) Optimization of Cutting Parameters and Result Predictions with Response Surface Methodology, Individual and Ensemble Machine Learning Algorithms in End Milling of AISI 321. Arabian Journal for Science and Engineering.
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János Kundrák, Csaba Felhő & Antal Nagy. (2022) Analysis and Prediction of Roughness of Face Milled Surfaces using CAD Model. Manufacturing Technology 22:5, pages 558-572.
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Zvikomborero Hweju & Khaled Abou-El-Hossein. (2022) Bayesian Network Modelling: Predictor Impact Assessment in Surface Roughness Prediction. Solid State Phenomena 331, pages 53-60.
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Mehmet Altuğ, Mehmet Erdem, Cetin Ozay & Oguz Bozkır. (2022) Surface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networks. Materials Testing 58:3, pages 189-199.
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Carlos Villa‐Blanco, Pedro Larrañaga & Concha Bielza. (2021) Multidimensional continuous time Bayesian network classifiers. International Journal of Intelligent Systems 36:12, pages 7839-7866.
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Binghao Fu, Zhenyu Wu & Juchuan Guo. (2020) Remaining Useful Life Prediction under Multiple Operation Conditions Based on Domain Adaptive Sparse Auto-Encoder. Remaining Useful Life Prediction under Multiple Operation Conditions Based on Domain Adaptive Sparse Auto-Encoder.
X. Wang, R. Eisseler & H.-C. Moehring. (2020) Prediction and optimization of machining results and parameters in drilling by using Bayesian networks. Production Engineering 14:3, pages 373-383.
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Victor Flores & Brian Keith. (2019) Gradient Boosted Trees Predictive Models for Surface Roughness in High-Speed Milling in the Steel and Aluminum Metalworking Industry. Complexity 2019, pages 1-15.
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Maciej Grzenda & Andres Bustillo. (2018) Semi-supervised roughness prediction with partly unlabeled vibration data streams. Journal of Intelligent Manufacturing 30:2, pages 933-945.
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Suman Kumari, Hanuma Reddy Tiyyagura, Timothy E.L. Douglas, Elbeshary A.A. Mohammed, Annemie Adriaens, Regina Fuchs-Godec, M.K. Mohan & Andre G. Skirtach. (2018) ANN prediction of corrosion behaviour of uncoated and biopolymers coated cp-Titanium substrates. Materials & Design 157, pages 35-51.
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Dragan Djurdjanovic, Laine Mears, Farbod Akhavan Niaki, Asad Ul Haq & Lin Li. (2018) State of the Art Review on Process, System, and Operations Control in Modern Manufacturing. Journal of Manufacturing Science and Engineering 140:6.
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David Lechevalier, Anantha Narayanan, Sudarsan Rachuri & Sebti Foufou. (2018) A methodology for the semi-automatic generation of analytical models in manufacturing. Computers in Industry 95, pages 54-67.
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Saideep Nannapaneni, Anantha Narayanan, Ronay Ak, David Lechevalier, Thurston Sexton, Sankaran Mahadevan & Yung-Tsun Tina Lee. (2018) Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing. Smart and Sustainable Manufacturing Systems 2:1, pages 20180018.
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Víctor Flores, Maritza Correa & Yadira Quiñonez. 2017. Natural and Artificial Computation for Biomedicine and Neuroscience. Natural and Artificial Computation for Biomedicine and Neuroscience 233 242 .
Ricardo Coppel, Jose V. Abellan-Nebot, Hector R. Siller, Ciro A. Rodriguez & Federico Guedea. (2015) Adaptive control optimization in micro-milling of hardened steels—evaluation of optimization approaches. The International Journal of Advanced Manufacturing Technology 84:9-12, pages 2219-2238.
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Álvar Arnaiz-González, Asier Fernández-Valdivielso, Andres Bustillo & Luis Norberto López de Lacalle. (2015) Using artificial neural networks for the prediction of dimensional error on inclined surfaces manufactured by ball-end milling. The International Journal of Advanced Manufacturing Technology 83:5-8, pages 847-859.
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David Lechevalier, Anantha Narayanan, Sudarsan Rachuri, Sebti Foufou & Y. Tina Lee. 2016. Product Lifecycle Management for Digital Transformation of Industries. Product Lifecycle Management for Digital Transformation of Industries 146 157 .
Dinh Son Nguyen. (2015) Application of Bayesian networks for product quality management in a multistage manufacturing process. Application of Bayesian networks for product quality management in a multistage manufacturing process.
Amin Jahromi Torabi, Meng Joo Er, Xiang Li, Beng Siong Lim, Lianyin Zhai, Richard J. Oentaryo, Gan Oon Peen & Jacek M. Zurada. (2015) A Survey on Artificial Intelligence-Based Modeling Techniques for High Speed Milling Processes. IEEE Systems Journal 9:3, pages 1069-1080.
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Mingwei Wang & Jingtao Zhou. (2014) A Bayesian network-based classifier for machining error prediction. A Bayesian network-based classifier for machining error prediction.
L. M. Torres-Treviño, I. Escamilla, B. Gonzalez, R. Praga-Alejo & P. Pérez-Villanueva. (2013) Modeling cutting machining process using symbolic regression $\alpha $ - $\beta $. The International Journal of Advanced Manufacturing Technology 67:9-12, pages 2351-2366.
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Maciej Grzenda & Andres Bustillo. (2013) The evolutionary development of roughness prediction models. Applied Soft Computing 13:5, pages 2913-2922.
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Kang He, Min Ping Jia & Zhuan Zhe Zhao. (2012) Quality Monitoring of Surface Roughness and Roundness Using Hidden Markov Model. Advanced Materials Research 630, pages 308-314.
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Andres Bustillo & Maritza Correa. (2011) Using artificial intelligence to predict surface roughness in deep drilling of steel components. Journal of Intelligent Manufacturing 23:5, pages 1893-1902.
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Susana Ferreiro, Basilio Sierra, Itziar Irigoien & Eneko Gorritxategi. (2011) A Bayesian network for burr detection in the drilling process. Journal of Intelligent Manufacturing 23:5, pages 1463-1475.
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José-Francisco Díez-Pastor, Andres Bustillo, Guillem Quintana & César García-Osorio. (2012) Boosting Projections to improve surface roughness prediction in high-torque milling operations. Soft Computing 16:8, pages 1427-1437.
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Susana Ferreiro & Basilio Sierra. (2011) Comparison of machine learning algorithms for optimization and improvement of process quality in conventional metallic materials. The International Journal of Advanced Manufacturing Technology 60:1-4, pages 237-249.
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Guillem Quintana, Thomas Rudolf, Joaquim Ciurana & Christian Brecher. (2011) Surface roughness prediction through internal kernel information and external accelerometers using artificial neural networks. Journal of Mechanical Science and Technology 25:11, pages 2877-2886.
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Andres Bustillo, José-Francisco Díez-Pastor, Guillem Quintana & César García-Osorio. (2011) Avoiding neural network fine tuning by using ensemble learning: application to ball-end milling operations. The International Journal of Advanced Manufacturing Technology 57:5-8, pages 521-532.
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G. Quintana, M. L. Garcia-Romeu & J. Ciurana. (2009) Surface roughness monitoring application based on artificial neural networks for ball-end milling operations. Journal of Intelligent Manufacturing 22:4, pages 607-617.
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Susana Ferreiro, Basilio Sierra, Itziar Irigoien & Eneko Gorritxategi. (2011) Data mining for quality control: Burr detection in the drilling process. Computers & Industrial Engineering 60:4, pages 801-810.
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Christian Brecher, Guillem Quintana, Thomas Rudolf & Joaquim Ciurana. (2010) Use of NC kernel data for surface roughness monitoring in milling operations. The International Journal of Advanced Manufacturing Technology 53:9-12, pages 953-962.
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Víctor M. Flores, Maritza Correa & José R. Alique. (2011) Modelo Pre-Proceso de predicción de la Calidad Superficial en Fresado a Alta Velocidad basado en Softcomputing. Revista Iberoamericana de Automática e Informática Industrial RIAI 8:1, pages 38-43.
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Susana Ferreiro, Basilio Sierra, Eneko Gorritxategi & Itziar Irigoien. (2010) Bayesian Network for quality control in the drilling process. IFAC Proceedings Volumes 43:4, pages 264-269.
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Amin J. Torabi, Er Meng Joo, Li Xiang, Lim Beng Siong, Zhai Lianyin, Phua Si Jie, Zhou Junhong, San Lin, Huang Sheng & Jose Thomas Thayil Tijo. (2009) A survey on artificial intelligence technologies in modeling of High Speed end-milling processes. A survey on artificial intelligence technologies in modeling of High Speed end-milling processes.
Raquel Redondo, Pedro Santos, Andres Bustillo, Javier Sedano, José Ramón Villar, Maritza Correa, José Ramón Alique & Emilio Corchado. 2009. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living 1282 1291 .

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