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Special Issue: Machine Learning Applications in Manufacturing – Part I
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Journal Articles

Automated Classification of Manufacturing Process Capability Utilizing Part Shape, Material, and Quality Attributes

Changxuan Zhao, Mahmoud Dinar, Shreyes N. Melkote
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021011.
Paper No: JCISE-19-1158
https://doi.org/10.1115/1.4045410
Published Online: January 8, 2020
View Article titled, Automated Classification of Manufacturing Process Capability Utilizing Part Shape, Material, and Quality Attributes
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Topics: Manufacturing, Shapes, Design
Journal Articles

NBLSTM: Noisy and Hybrid Convolutional Neural Network and BLSTM-Based Deep Architecture for Remaining Useful Life Estimation

Ali Al-Dulaimi, Soheil Zabihi, Amir Asif, Arash Mohammed
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021012.
Paper No: JCISE-19-1182
https://doi.org/10.1115/1.4045491
Published Online: January 8, 2020
View Article titled, NBLSTM: Noisy and Hybrid Convolutional Neural Network and BLSTM-Based Deep Architecture for Remaining Useful Life Estimation
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Topics: Artificial neural networks, Service life (Equipment), NASA, Robustness, Architecture, Noise (Sound)
Journal Articles

Dilated Convolution Neural Network for Remaining Useful Life Prediction

Xin Xu, Qianhui Wu, Xiu Li, Biqing Huang
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021004.
Paper No: JCISE-19-1169
https://doi.org/10.1115/1.4045293
Published Online: January 3, 2020
View Article titled, Dilated Convolution Neural Network for Remaining Useful Life Prediction
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Topics: Artificial neural networks, Filters, Sensors, Service life (Equipment), Feature extraction
Journal Articles

A Coarse-Grained Regularization Method of Convolutional Kernel for Molten Pool Defect Identification

Tianyuan Liu, Jinsong Bao, Junliang Wang, Yiming Zhang
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021005.
Paper No: JCISE-19-1148
https://doi.org/10.1115/1.4045294
Published Online: January 3, 2020
View Article titled, A Coarse-Grained Regularization Method of Convolutional Kernel for Molten Pool Defect Identification
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Topics: Algorithms, Artificial intelligence, Artificial neural networks, Engineering systems and industry applications, Machine learning, Machinery, Testing, Weight (Mass), Welding
Journal Articles

An Integrated Target Acquisition Approach and Graphical User Interface Tool for Parallel Manipulator Assembly

Haodong Chen, Zhiqiang Teng, Zheng Guo, Ping Zhao
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021006.
Paper No: JCISE-19-1184
https://doi.org/10.1115/1.4045411
Published Online: January 3, 2020
View Article titled, An Integrated Target Acquisition Approach and Graphical User Interface Tool for Parallel Manipulator Assembly
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Topics: Algorithms, Collisions (Physics), Graphical user interfaces, Machine components, Machinery, Manipulators, Manufacturing, Robots, Shapes, Support vector machines
Journal Articles

Failure Prognosis of Complex Equipment With Multistream Deep Recurrent Neural Network

Yonghe Su, Fei Tao, Jian Jin, Tian Wang, Qingguo Wang, Lei Wang
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021007.
Paper No: JCISE-19-1118
https://doi.org/10.1115/1.4045445
Published Online: January 3, 2020
View Article titled, Failure Prognosis of Complex Equipment With Multistream Deep Recurrent Neural Network
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Topics: Artificial neural networks, Bearings, Failure, Signals, Vibration, Simulation, Machine learning
Journal Articles

A Simulation Data-Driven Design Approach for Rapid Product Optimization

Yanli Shao, Huawei Zhu, Rui Wang, Ying Liu, Yusheng Liu
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021008.
Paper No: JCISE-19-1176
https://doi.org/10.1115/1.4045527
Published Online: January 3, 2020
View Article titled, A Simulation Data-Driven Design Approach for Rapid Product Optimization
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Topics: Algorithms, Design, Optimization, Simulation, Data mining, Optimization algorithms, Weight (Mass)
Journal Articles

An Integrative Machine Learning Method to Improve Fault Detection and Productivity Performance in a Cyber-Physical System

Ming-Chuan Chiu, Chien-De Tsai, Tung-Lung Li
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021009.
Paper No: JCISE-19-1235
https://doi.org/10.1115/1.4045663
Published Online: January 3, 2020
View Article titled, An Integrative Machine Learning Method to Improve Fault Detection and Productivity Performance in a Cyber-Physical System
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Topics: Flaw detection, Machine learning, Machinery, Maintenance, Printing, Sensors, Time series, Algorithms, Engineers, Manufacturing
Journal Articles

Image Data-Based Surface Texture Characterization and Prediction Using Machine Learning Approaches for Additive Manufacturing

V. Akhil, G. Raghav, N. Arunachalam, D. S. Srinivas
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021010.
Paper No: JCISE-19-1222
https://doi.org/10.1115/1.4045719
Published Online: January 3, 2020
View Article titled, Image Data-Based Surface Texture Characterization and Prediction Using Machine Learning Approaches for Additive Manufacturing
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Topics: Additive manufacturing, Surface roughness, Surface texture, Texture (Materials), Machine learning, Lasers, Artificial neural networks, Statistics
Journal Articles

Thermal Error Modeling of Feed Axis in Machine Tools Using Particle Swarm Optimization-Based Generalized Regression Neural Network

Guolong Li, Hao Ke, Chuanzhen Li, Biao Li
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021003.
Paper No: JCISE-19-1179
https://doi.org/10.1115/1.4045292
Published Online: December 11, 2019
View Article titled, Thermal Error Modeling of Feed Axis in Machine Tools Using Particle Swarm Optimization-Based Generalized Regression Neural Network
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Topics: Artificial neural networks, Errors, Machine tools, Optimization, Particle swarm optimization, Particulate matter, Temperature, Modeling, Neural network models
Journal Articles

Ferrograph Analysis With Improved Particle Segmentation and Classification Methods

Shuo Wang, Tonghai Wu, Kunpeng Wang, Thompson Sarkodie-Gyan
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021001.
Paper No: JCISE-19-1157
https://doi.org/10.1115/1.4045291
Published Online: December 11, 2019
View Article titled, Ferrograph Analysis With Improved Particle Segmentation and Classification Methods
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Topics: Particulate matter, Wear, Image segmentation, Fatigue
Journal Articles

Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing

Ziyang Zhang, Laxmi Poudel, Zhenghui Sha, Wenchao Zhou, Dazhong Wu
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021002.
Paper No: JCISE-19-1204
https://doi.org/10.1115/1.4045290
Published Online: December 11, 2019
View Article titled, Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing
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Topics: Additive manufacturing, Tensile strength, Modeling, Shells, Mechanical properties