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Proceedings Papers

Machine Fault Diagnosis Through a Recursive Optimal Pairwise Linear Discriminant Function Method

Shuxin Gu, Jun Ni, Jingxia Yuan, Jay Lee

Proc. ASME. IMECE98, Manufacturing Science and Engineering, 547-554, November 15–20, 1998

Paper No: IMECE1998-1068

DOI: https://doi.org/10.1115/IMECE1998-1068

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Topics: Fault diagnosis, Machinery, Pattern recognition, Artificial neural networks, Failure, Feedforward control

Proceedings Papers

Finite Element Analysis of Orthogonal Cutting With Blunt-Edge Tool

Y. Richard Chen, Jun Ni

Proc. ASME. IMECE98, Manufacturing Science and Engineering, 853-866, November 15–20, 1998

Paper No: IMECE1998-1101

DOI: https://doi.org/10.1115/IMECE1998-1101

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Topics: Cutting, Finite element analysis, Stress, Deformation, Carbon, Finite element model, Flow (Dynamics), Machining, Materials properties, Modeling

Proceedings Papers

Adaptive Influence Coefficient Control of Single-Plane Active Balancing Systems for Rotating Machinery

Stephen W. Dyer, Jun Ni

Proc. ASME. IMECE99, Manufacturing Science and Engineering, 747-755, November 14–19, 1999

Paper No: IMECE1999-0737

DOI: https://doi.org/10.1115/IMECE1999-0737

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Topics: Machinery, Adaptive control, Vibration, Dynamics (Mechanics), Machine tools, Modeling, Noise (Sound), Robustness, Rotation, Stability

Proceedings Papers

Diagnosis of Multiple Simultaneous Faults in Manufacturing Systems

Wei Li, S. Jack Hu, Jun Ni

Proc. ASME. IMECE99, Manufacturing Science and Engineering, 581-588, November 14–19, 1999

Paper No: IMECE1999-0718

DOI: https://doi.org/10.1115/IMECE1999-0718

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Topics: Manufacturing systems, Fault diagnosis, Modeling, Simulation, Welding

Proceedings Papers

A Self-Calibration Method for Robotic Measurement System

Chunhe Gong, Jingxia Yuan, Jun Ni

Proc. ASME. IMECE99, Manufacturing Science and Engineering, 879-888, November 14–19, 1999

Paper No: IMECE1999-0753

DOI: https://doi.org/10.1115/IMECE1999-0753

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Topics: Calibration, Measurement systems, Robotics, Sensors

Proceedings Papers

Machine-Tool Chatter Suppression by Multi-Level Random Spindle Speed Variation

Alpay Yilmaz, Emad AL-Regib, Jun Ni

Proc. ASME. IMECE99, Manufacturing Science and Engineering, 897-905, November 14–19, 1999

Paper No: IMECE1999-0755

DOI: https://doi.org/10.1115/IMECE1999-0755

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Topics: Chatter, Machine tools, Machining, Computer simulation, Signals, Stability

Proceedings Papers

A Strategy for the Sensor Placement Optimization for Machine Thermal Error Compensation

Youji Ma, Jingxia Yuan, Jun Ni

Proc. ASME. IMECE99, Manufacturing Science and Engineering, 629-637, November 14–19, 1999

Paper No: IMECE1999-0724

DOI: https://doi.org/10.1115/IMECE1999-0724

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Topics: Error compensation, Machinery, Optimization, Sensor placement, Machine tools, Errors, Sensors, Thermal deformation, Thermal expansion, Chain

Journal Articles

Machine Learning for Diagnosis of Event Synchronization Faults in Discrete Manufacturing Systems

Joseph Cohen, Baoyang Jiang, Jun Ni

J. Manuf. Sci. Eng. July 2022, 144(7): 071006.

Paper No: MANU-21-1315

DOI: https://doi.org/10.1115/1.4052762

Published Online: December 8, 2021

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Topics: Fault diagnosis, Machine learning, Signals, Synchronization, Failure, Manufacturing systems, Programmable controllers, Delays

Journal Articles

Semi-Supervised Learning for Anomaly Classification Using Partially Labeled Subsets

Joseph Cohen, Jun Ni

J. Manuf. Sci. Eng. June 2022, 144(6): 061008.

Paper No: MANU-21-1317

DOI: https://doi.org/10.1115/1.4052761

Published Online: December 3, 2021

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Topics: Algorithms, Computer-aided engineering, Dimensions, Feature extraction, Machine learning, Principal component analysis, Integrated circuit fabrication, Artificial intelligence

Proceedings Papers

Stream of Variation Based Analysis and Synthesis of Measurement Schemes in Multi-Station Machining Systems

Dragan Djurdjanovic, Jun Ni

Proc. ASME. IMECE2001, Manufacturing Engineering, 297-304, November 11–16, 2001

Paper No: IMECE2001/MED-23333

DOI: https://doi.org/10.1115/IMECE2001/MED-23333

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Topics: Machining, Errors, Measurement uncertainty, Modeling, Tradeoffs

Proceedings Papers

Modal Inverse Frequency Response Heat Transfer Analysis for Estimation of Machine Tool Transient Thermal Loads

Youji Ma, Jingxia Yuan, Jun Ni

Proc. ASME. IMECE2001, Manufacturing Engineering, 289-296, November 11–16, 2001

Paper No: IMECE2001/MED-23332

DOI: https://doi.org/10.1115/IMECE2001/MED-23332

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Topics: Frequency response, Heat transfer, Machine tools, Stress, Transients (Dynamics), Spectra (Spectroscopy), Errors, Temperature measurement, Computer software, Deformation

Proceedings Papers

Dynamic Modeling for Machine Tool Thermal Error Compensation

Hong Yang, Jingxia Yuan, Jun Ni

Proc. ASME. IMECE2001, Manufacturing Engineering, 281-288, November 11–16, 2001

Paper No: IMECE2001/MED-23331

DOI: https://doi.org/10.1115/IMECE2001/MED-23331

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Topics: Dynamic modeling, Error compensation, Machine tools, Errors, Modeling, Robustness, Dynamic models, Deformation, Dynamic systems, Machinery

Proceedings Papers

Active Balancing and Optimal Balancing Plane Selection of Rotors During Acceleration

Shiyu Zhou, Kwang-keun Shin, Stephen W. Dyer, Jianjun Shi, Jun Ni

Proc. ASME. IMECE2001, Dynamic Systems and Control, 461-468, November 11–16, 2001

Paper No: IMECE2001/DSC-24558

DOI: https://doi.org/10.1115/IMECE2001/DSC-24558

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Topics: Rotors, Vibration, Actuators, Algorithms, Gain scheduling, Machinery

Proceedings Papers

A Semi-Supervised Multiclass Anomaly Detection Approach for Partially Labeled In-Process Measurement Data

Joseph Cohen, Jun Ni

Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A004, June 21–25, 2021

Paper No: MSEC2021-63465

DOI: https://doi.org/10.1115/MSEC2021-63465

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Topics: Algorithms, Artificial intelligence, Dimensions, Feature extraction, Flaw detection, Integrated circuit fabrication, Machine learning, Principal component analysis

Proceedings Papers

Research on Flow and Heat Transfer Characteristics of Multiple Impinging Jets on a Moving Conveyor Belt

Rui Liu, Yu Sun, Jun Ni

Proc. ASME. IMECE2020, Volume 10: Fluids Engineering, V010T10A028, November 16–19, 2020

Paper No: IMECE2020-23272

DOI: https://doi.org/10.1115/IMECE2020-23272

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Topics: Conveyor belts, Flow (Dynamics), Heat transfer, Jets

Proceedings Papers

Experimental Analysis of Material Squeeze Factor in Two-Point Incremental Forming of AL 7075-O

Ankush Bansal, Randy Cheng, Mihaela Banu, Alan Taub, Jun Ni

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A027, September 3, 2020

Paper No: MSEC2020-8527

DOI: https://doi.org/10.1115/MSEC2020-8527

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Topics: Experimental analysis, Forming equipment (Packaging), Machinery, Manufacturing, Shapes, Sheet metal

Proceedings Papers

Fault Diagnosis of Timed Event Systems: An Exploration of Machine Learning Methods

Joseph Cohen, Baoyang Jiang, Jun Ni

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A029, September 3, 2020

Paper No: MSEC2020-8360

DOI: https://doi.org/10.1115/MSEC2020-8360

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Topics: Fault diagnosis, Machine learning, Principal component analysis, Programmable controllers, Algorithms, Signals, Artificial neural networks, Failure, Integrated circuit fabrication, Manufacturing

Proceedings Papers

High Precision Tracking of Roll-to-Roll Manufacturing Processes

Zhiyi Chen, Baoyang Jiang, Jun Ni

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A030, September 3, 2020

Paper No: MSEC2020-8392

DOI: https://doi.org/10.1115/MSEC2020-8392

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Topics: Control equipment, Manufacturing, Predictive control, Quadratic programming, Robustness, Rollers, Simulation, Stability, Tension, Uncertainty

Proceedings Papers

Machine Learning Based Novelty Detection Methods for Progressive Stamping Process Health Monitoring

Tianchen Qiu, Xingjian Lai, Jun Ni

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A034, September 3, 2020

Paper No: MSEC2020-8496

DOI: https://doi.org/10.1115/MSEC2020-8496

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Topics: Machine learning, Machinery, Metal stamping, Support vector machines

Journal Articles

Algorithm for Accumulating Part Mating Gaps to Evaluate Solid and Fluid Performances

Jun Ni, Rui Liu, Yu Sun

J. Mech. Des. April 2021, 143(4): 043501.

Paper No: MD-20-1194

DOI: https://doi.org/10.1115/1.4047910

Published Online: October 28, 2020

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Topics: Algebra, Design, Fluids, Manufacturing, Turbines, Blades, Algorithms, Displacement

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Journal citation

NARROW

Machine Fault Diagnosis Through a Recursive Optimal Pairwise Linear Discriminant Function Method

Finite Element Analysis of Orthogonal Cutting With Blunt-Edge Tool

Adaptive Influence Coefficient Control of Single-Plane Active Balancing Systems for Rotating Machinery

Diagnosis of Multiple Simultaneous Faults in Manufacturing Systems

A Self-Calibration Method for Robotic Measurement System

Machine-Tool Chatter Suppression by Multi-Level Random Spindle Speed Variation

A Strategy for the Sensor Placement Optimization for Machine Thermal Error Compensation

Machine Learning for Diagnosis of Event Synchronization Faults in Discrete Manufacturing Systems

Semi-Supervised Learning for Anomaly Classification Using Partially Labeled Subsets

Stream of Variation Based Analysis and Synthesis of Measurement Schemes in Multi-Station Machining Systems

Modal Inverse Frequency Response Heat Transfer Analysis for Estimation of Machine Tool Transient Thermal Loads

Dynamic Modeling for Machine Tool Thermal Error Compensation

Active Balancing and Optimal Balancing Plane Selection of Rotors During Acceleration

A Semi-Supervised Multiclass Anomaly Detection Approach for Partially Labeled In-Process Measurement Data

Research on Flow and Heat Transfer Characteristics of Multiple Impinging Jets on a Moving Conveyor Belt

Experimental Analysis of Material Squeeze Factor in Two-Point Incremental Forming of AL 7075-O

Fault Diagnosis of Timed Event Systems: An Exploration of Machine Learning Methods

High Precision Tracking of Roll-to-Roll Manufacturing Processes

Machine Learning Based Novelty Detection Methods for Progressive Stamping Process Health Monitoring

Algorithm for Accumulating Part Mating Gaps to Evaluate Solid and Fluid Performances

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