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Proceedings Papers

Dimensional Deviation Prediction Model Based on Scale and Material Concentration Effects for LPBF Process

Sabrine Ben Amor, Floriane Zongo, Borhen Louhichi, Antoine Tahan, Vladimir Brailovski

Proc. ASME. IAM2022, 2022 International Additive Manufacturing Conference, V001T02A005, October 19–20, 2022

Paper No: IAM2022-93969

DOI: https://doi.org/10.1115/IAM2022-93969

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Topics: Additive manufacturing, Finite element analysis, Lasers, Machinery, Manufacturing, Numerical analysis, Product development, Stairs, Surface roughness

Proceedings Papers

In-Process Mechanical Working of Additive Manufactured Rene 41

William Sean James, Supriyo Ganguly, Goncalo Pardal

Proc. ASME. IAM2022, 2022 International Additive Manufacturing Conference, V001T02A008, October 19–20, 2022

Paper No: IAM2022-94060

DOI: https://doi.org/10.1115/IAM2022-94060

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Topics: Additive manufacturing, Shot peening, Alloys, Flight, Heat, Temperature, Creep, Defense industry, Elastic moduli, Hammers

Proceedings Papers

Machine Setup Abnormality Detection Using Machine Vision and Deep Learning

Sahil J. Choudhari, Swarit Anand Singh, Aitha Sudheer Kumar, K. A. Desai

Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T04A009, June 27–July 1, 2022

Paper No: MSEC2022-85519

DOI: https://doi.org/10.1115/MSEC2022-85519

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Topics: Machinery

Proceedings Papers

Visual Servo Based Trajectory Planning for Fast and Accurate Sheet Pick and Place Operations

Omey M. Manyar, Alec Kanyuck, Bharat Deshkulkarni, Satyandra K. Gupta

Paper No: MSEC2022-85952

DOI: https://doi.org/10.1115/MSEC2022-85952

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Topics: Servomechanisms, Trajectories (Physics), Machinery, Robots, Suction, Textiles, Aerospace industry, Composite materials, Control algorithms, Errors

Proceedings Papers

Vision-Sensor Fusion-Based Low-Cost Dimension Measurement System for Machining Shop Floor

Swarit Anand Singh, Aitha Sudheer Kumar, Pratik C. Sorathiya, K. A. Desai

Paper No: MSEC2022-85442

DOI: https://doi.org/10.1115/MSEC2022-85442

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Topics: Dimensions, Machinery, Machining, Measurement systems, Sensors

Proceedings Papers

Evaluation of Process Parameters Modifications on Directed Energy Deposition Manufactured Parts Obtained in a Hybrid Additive Manufacturing Machine

Ana Beatriz B. Henriques, Paola L. de Aguiar, Raphael G. dos Santos, Joice Miagava

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A030, June 27–July 1, 2022

Paper No: MSEC2022-85315

DOI: https://doi.org/10.1115/MSEC2022-85315

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Topics: Additive manufacturing, Machinery, Lasers, Computer numerical control machine tools, Milling, Gas flow, Heat transfer, Machine tools, Machining, Manufacturing

Proceedings Papers

A Novel Welding Method for Repairing Surface Defects of Large-Type Rotary Machinery Based on Line Structured Light Detection

Hao Fu, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Shijie Liu, Shaojun Wang

Paper No: MSEC2022-85527

DOI: https://doi.org/10.1115/MSEC2022-85527

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Topics: Machinery, Maintenance, Robots, Sensors, Trajectories (Physics), Welding

Proceedings Papers

Digital Twin-Based Tool State Prognosis Model for Drilling Machines

Sunidhi Dayam, K. A. Desai

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A039, June 27–July 1, 2022

Paper No: MSEC2022-85449

DOI: https://doi.org/10.1115/MSEC2022-85449

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Topics: Digital twin, Drilling, Machinery

Proceedings Papers

Incremental Sheet Forming of the WKU Big Red Mascot

Asghar Rezasoltani, Matthew Crocker, Jeremy Rice, Avery Black

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A001, June 27–July 1, 2022

Paper No: MSEC2022-78600

DOI: https://doi.org/10.1115/MSEC2022-78600

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Topics: Computer programming, Computer-aided design, Design, Gages, Machinery, Manufacturing, Robotics, Shapes, Springs, Surface quality

Proceedings Papers

Design and Manufacturing of a Functionally Graded Porous Dental Implant

Rana Dabaja, Bogdan I. Popa, Sun-Yung Bak, Gustavo Mendonca, Mihaela Banu

Paper No: MSEC2022-85426

DOI: https://doi.org/10.1115/MSEC2022-85426

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Topics: Additive manufacturing, Design, Manufacturing, Bone, Diseases, Melting, Resolution (Optics), Disks, Failure, Geometry

Proceedings Papers

Machine Vision Tracking and Automation of a Microrobot (sAFAM)

Colin Warn, Andriy Sherehiy, Moath Alqatamin, Brooke Ritz, Ruoshi Zhang, Sri S. Chowdhury, Danming Wei, Dan O. Popa

Paper No: MSEC2022-85424

DOI: https://doi.org/10.1115/MSEC2022-85424

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Topics: Machinery, Manufacturing

Proceedings Papers

Anomaly Scoring Model for Diagnosis on Machine Condition and Health Management

Byung Gun Joung, Zhongtian Li, John W. Sutherland

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A017, June 27–July 1, 2022

Paper No: MSEC2022-85459

DOI: https://doi.org/10.1115/MSEC2022-85459

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Topics: Machine learning, Machinery, Manufacturing, Pulse width modulation, Maintenance, Manufacturing systems, Failure, Vibration, Artificial intelligence, Compressors

Proceedings Papers

Analysis of Dynamic Parameter for Gantry Mobile-Type Dual-Drive Machine

Min Hu, Hong Lu, Qi Liu, Jiashun Dai, Ben Wang, Shaojun Wang

Paper No: MSEC2022-85526

DOI: https://doi.org/10.1115/MSEC2022-85526

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Topics: Gravity (Force), Machinery

Proceedings Papers

A Machinability Study of Coated Inserts for Turning Ti-6Al-4V

Ryan M. Khawarizmi, Yang Guo, Thomas R. Bieler, Patrick Kwon

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A053, June 27–July 1, 2022

Paper No: MSEC2022-85632

DOI: https://doi.org/10.1115/MSEC2022-85632

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Topics: Alloys, Carbide cutting tools, Chemical stability, Coatings, Cutting, Dynamometers, Laser scanning microscopy, Machinability, Machinery, Machining

Proceedings Papers

Extracting the In-Process Structural Dynamics Parameters in Micro-Milling Operations

Maryam Hashemitaheri, Rinku Mittal, Harish Cherukuri, Ramesh Singh

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A052, June 27–July 1, 2022

Paper No: MSEC2022-85621

DOI: https://doi.org/10.1115/MSEC2022-85621

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Topics: Micromilling, Structural dynamics, Cutting, Physics, Stability, Machinery, Newton's method, Chatter, Dynamics (Mechanics), Flow (Dynamics)

Proceedings Papers

The Development and Validation of a Novel Thread Forming Fastener for High Strength Steel Applications

Brandt J. Ruszkiewicz, Eric Breidenbaugh, Gene Simpson

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A006, June 27–July 1, 2022

Paper No: MSEC2022-81781

DOI: https://doi.org/10.1115/MSEC2022-81781

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Topics: Fasteners, High strength steel, Joining, Thread, Steel, Design, Heat, Screws, Simulation, Tensile strength

Proceedings Papers

Development and Evaluation of a Computer Vision System for Assembly Bolt Pattern Traceability and Poka-Yoke

Eric Kozikowski, Nathan W. Hartman, Jorge D. Camba

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A023, June 27–July 1, 2022

Paper No: MSEC2022-85678

DOI: https://doi.org/10.1115/MSEC2022-85678

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Topics: Computers, Machinery, Manufacturing

Proceedings Papers

Immersive Virtual Reality Training With Error Management for CNC Milling Set-Up

Matt Ryan, Yiwen Wang, Qinqin Xiao, Rui Liu, Yunbo Zhang

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A027, June 27–July 1, 2022

Paper No: MSEC2022-85770

DOI: https://doi.org/10.1115/MSEC2022-85770

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Topics: Computer numerical control machine tools, Errors, Milling, Virtual reality, Training programs, Machinery, Machining, Machining centers, Mentoring, Safety

Proceedings Papers

Machine Learning-Based Cutting Constant Estimation for Mechanistic Force Models of End Milling Operation

Shubham Vaishnav, K. A. Desai

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A048, June 27–July 1, 2022

Paper No: MSEC2022-85587

DOI: https://doi.org/10.1115/MSEC2022-85587

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Topics: Cutting, Machine learning, Machinery, Milling

Proceedings Papers

Process Mechanics – a Guide for Industry 4.0: Modelling Cutting of Nimonic 90 and Ti-6Al-4V

W. Lortz, Radu Pavel

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A037, June 27–July 1, 2022

Paper No: MSEC2022-85443

DOI: https://doi.org/10.1115/MSEC2022-85443

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Topics: Cutting, Hardening, Modeling, Temperature, Deformation, Simulation, Stress, Alloys, Artificial intelligence, Computers

2 3 4 5

NARROW

Dimensional Deviation Prediction Model Based on Scale and Material Concentration Effects for LPBF Process

In-Process Mechanical Working of Additive Manufactured Rene 41

Machine Setup Abnormality Detection Using Machine Vision and Deep Learning

Visual Servo Based Trajectory Planning for Fast and Accurate Sheet Pick and Place Operations

Vision-Sensor Fusion-Based Low-Cost Dimension Measurement System for Machining Shop Floor

Evaluation of Process Parameters Modifications on Directed Energy Deposition Manufactured Parts Obtained in a Hybrid Additive Manufacturing Machine

A Novel Welding Method for Repairing Surface Defects of Large-Type Rotary Machinery Based on Line Structured Light Detection

Digital Twin-Based Tool State Prognosis Model for Drilling Machines

Incremental Sheet Forming of the WKU Big Red Mascot

Design and Manufacturing of a Functionally Graded Porous Dental Implant

Machine Vision Tracking and Automation of a Microrobot (sAFAM)

Anomaly Scoring Model for Diagnosis on Machine Condition and Health Management

Analysis of Dynamic Parameter for Gantry Mobile-Type Dual-Drive Machine

A Machinability Study of Coated Inserts for Turning Ti-6Al-4V

Extracting the In-Process Structural Dynamics Parameters in Micro-Milling Operations

The Development and Validation of a Novel Thread Forming Fastener for High Strength Steel Applications

Development and Evaluation of a Computer Vision System for Assembly Bolt Pattern Traceability and Poka-Yoke

Immersive Virtual Reality Training With Error Management for CNC Milling Set-Up

Machine Learning-Based Cutting Constant Estimation for Mechanistic Force Models of End Milling Operation

Process Mechanics – a Guide for Industry 4.0: Modelling Cutting of Nimonic 90 and Ti-6Al-4V

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