TY - JOUR
T1 - A framework for process inspection of metal additive manufacturing
AU - Cheng, Chih Kun
AU - Liou, Frank
AU - Cheng, Yi Chien
AU - Shen, Sheng Chih
N1 - Funding Information:
The authors would like to thank the Ministry of Science and Technology (MOST) and Fisheries Agency, Council of Agriculture (FA.COA) for their support of the project [Grant Nos. MOST 107-2218-E-006-031-, MOST 107-2218-E-110-004-, and 107AS-14.2.7-FA-F1(3)]. Additionally, this research was, in part, supported by the Ministry of Education, Taiwan, Headquarters of Advancement to the Intelligent Manufacturing Center (iMRC), National Cheng Kung University (NCKU), and US National Science Foundation (CMMI 1625736).
Funding Information:
Yi-Chien Cheng received her B.S. degree in electrical engineering from National Changhua University of Education, Taiwan, in 2017. She is currently working toward her M.S. degree in the Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University, Tainan, Taiwan. Her research is on additive manufacturing (AM) under the supervision of Prof. Frank Liou. Because of her electrical engineering background, her research interests also include power systems and electric machinery. (zxc8069@yahoo.com.tw) Frank Liou is the Michael and Joyce Bytnar Professor of the Mechanical Engineering Department of Missouri University of Science and Technology. He has served as the Director of the Manufacturing Engineering Program at Missouri S&T since 1999. He has published a book on Rapid Prototyping along with over 300 technical papers. Dr. Liou’s research focuses on additive manufacturing (AM), including hybrid additive and subtractive processes, path planning, multiscale multiphysics process modeling, and AM process monitoring and control. His research has been funded by AFRL, DOE, NASA, NAVY, NSF, and many industrial partners. Dr. Liou has received several teaching, research, and service awards, including several best paper awards. Dr. Liou is a Fellow of ASME. (liou@mst.edu) Chih-Kun Cheng was born in 1963 in Tainan, Taiwan. He received his B.S. degree in industrial education in 1987 from National Taiwan Normal University. He received his M.S. degree in electrical engineering from National Cheng Kung University in 1999, and presently, he is in the Ph.D. program of the Department of Electrical Engineering, National Cheng Kung University. At present, he is the chairperson of the Department of Electrical Engineering, Far East University, Tainan, Taiwan. He has joined the transformer research group since conducting his M.S. thesis research. His major interests are in transformer technology, power systems, and electric machinery. (n2888122@yahoo.com.tw) Sheng-Chih Shen received his B.E. and M.S. degrees in automatic control engineering from Feng Chia University, Taiwan, in 1996 and 1998, respectively. He received his Ph.D. degree in 2002 from the Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan. He was a researcher in the MEMS division of the ITRI from 2002 to 2007, and a visiting scholar in the field of MEMS at Carnegie Mellon University from 2004 to 2005. He joined the Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University, Tainan, Taiwan, as a professor in 2018. His current research interests focus on PVDF fiber sensors, LED fishing lighting, and underwater optic lighting. (scshen@mail.ncku.edu.tw)
PY - 2019
Y1 - 2019
N2 - In this paper, we propose a process inspection framework for metal additive manufacturing (AM) processes. AM, also known as 3D printing, is the process of joining materials to make objects on the basis of 3D model data and is envisioned to play a strategic role in maintaining economic and scientific dominance. Different from conventional manufacturing methods, the AM process is a point-by-point and layer-by-layer manufacturing. Thus, there are many opportunities to generate a process error that can cause quality issues in an AM part. A systematic AM process inspection is needed to yield acceptable performance of the part. The critical parameters that may affect the part quality are identified before processing, during processing, and after processing. The framework of the initial AM process inspection is presented. By using basic sensors, such as a microhardness tester and profilometer, we can obtain critical information about an additive manufactured part.
AB - In this paper, we propose a process inspection framework for metal additive manufacturing (AM) processes. AM, also known as 3D printing, is the process of joining materials to make objects on the basis of 3D model data and is envisioned to play a strategic role in maintaining economic and scientific dominance. Different from conventional manufacturing methods, the AM process is a point-by-point and layer-by-layer manufacturing. Thus, there are many opportunities to generate a process error that can cause quality issues in an AM part. A systematic AM process inspection is needed to yield acceptable performance of the part. The critical parameters that may affect the part quality are identified before processing, during processing, and after processing. The framework of the initial AM process inspection is presented. By using basic sensors, such as a microhardness tester and profilometer, we can obtain critical information about an additive manufactured part.
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U2 - 10.18494/SAM.2019.2106
DO - 10.18494/SAM.2019.2106
M3 - Article
AN - SCOPUS:85062172759
VL - 31
SP - 411
EP - 420
JO - Sensors and Materials
JF - Sensors and Materials
SN - 0914-4935
IS - 2
ER -