The Dissimilar Self-Alignment Characteristics of Smaller Passive Components in the Length and Width Directions

Authors

  • Jingxi He State University of New York at Binghamton, Department of Systems Science and Industrial Engineering
  • Yuqiao Cen State University of New York at Binghamton, Department of Systems Science and Industrial Engineering
  • Yuanyuan Li State University of New York at Binghamton, Department of Systems Science and Industrial Engineering
  • Prof. Seungbae (SB) Park State University of New York at Binghamton, Department of Mechanical Engineering
  • Daehan Won, Ph.D. State University of New York at Binghamton, Department of Systems Science and Industrial Engineering

DOI:

https://doi.org/10.37665/smt.v34i2.16

Keywords:

SMT assembly, smaller passive components, self-alignment in length, self-alignment in width

Abstract

Motivation: As passive components’ size gets smaller, quality rejects due to overhang and misalignment after the reflow appear more frequently. This situation is partly because the pass-fail criterion is set based on the offset concerning the component dimensions. Therefore, understanding the self-alignment characteristics of electronic components becomes very critical for surface-mount assembly yield. This research investigates the dissimilarity of self-alignment in the length and width directions.

Approach: To avoid the argument of sample to sample variations, data are collected from 81 printed circuit boards (PCB) and 182,250 assembled components. Within a PCB, 25 different solder paste printing offset locations and 81 component placement offset settings are implemented. Component-placement positions before and after the reflow are monitored. The results are compared to identify different component sizes’ self-alignment characteristics in the length and width directions.

Key findings: The misalignment of smaller passive components, e.g., R0402M(0.40 mm × 0.20 mm), is worse than the larger component under the identical solder paste printing and component placement conditions. Furthermore, the self-alignment characteristic in the length direction of these passive components, e.g., R0402M, to R1005M (1.00 mm × 0.50 mm) is superior to that of width direction. The observations are not consistent with the results found in earlier research that reported on larger components, e.g., C0402M(0.40 mm × 0.20 mm), to C3216M(3.20 mm × 1.50 mm).

Author Biographies

Jingxi He, State University of New York at Binghamton, Department of Systems Science and Industrial Engineering

Jingxi He is currently a Ph.D. Candidate in the Department of Systems Science and Industrial Engineering, State University of New York at Binghamton. She holds a master’s degree in System Science from the State University of New York at Binghamton, NY, and a bachelor’s degree in Electrical Engineering from Hunan University, China. Her research interests include smart manufacturing, data analysis, and machine learning based advanced process control.

Yuqiao Cen, State University of New York at Binghamton, Department of Systems Science and Industrial Engineering

Yuqiao Cen received the B.S. degree in Engineering from Guangdong University of Technology, Guangdong, China, in 2015. Then she continued her education as a graduate student at New York University, in New York,
USA, in 2016, emphasizing urban science and informatics. She is currently a Ph.D. candidate at the Department of Systems Science and Industrial Engineering of Binghamton University - SUNY, in New York, USA. Her research interests are machine learning, big data, and time series data analytics.

Yuanyuan Li, State University of New York at Binghamton, Department of Systems Science and Industrial Engineering

Yuanyuan Li received her BS degree in China Jiliang University, China, in 2017 and received her MS degree in Industrial and System Engineering at the State University of New York at Binghamton in 2019. Currently, she is a Ph.D. candidate in Industrial and Systems Engineering at the State University of New York at Binghamton. Her research interests include machine learning, modeling and simulation, and system optimization. She conducted some research on deep learning-based medical image classification and is one of the final lists of the "Best paper competition" of DAIS track of the Institute of Industrial and Systems Engineers (IISE) Conference. She is now working on the research that developing artificial intelligence solutions in the surface mount technology assembly line. She is also a member of Alpha Pi Mu and IISE.

Prof. Seungbae (SB) Park, State University of New York at Binghamton, Department of Mechanical Engineering

Prof. Seungbae (SB) Park is a Professor of Mechanical engineering of the State University of New York at Binghamton. He is also the director of Integrated Electronics Engineering Center (IEEC), a New York State Center for Advanced Technology (CAT). He received his B.S. and M.S. from Seoul National University and Ph.D. at Purdue University in 1994. Dr. Park began his professional career at IBM. He was responsible for the reliability of IBM’s corporate flip chip technology in both leaded and lead-free solders and high performance packaging. Dr. SB Park started his academic career as a professor of mechanical engineering at the State University of New York at Binghamton in 2002. Professor Park is an expert in Modeling and Simulation for electronics components and systems integration. He has contributed in various 2.5D/3D package development, MEMS packaging, reliability assessment of assemblies and systems, and smart electronics manufacturing. He has more than 200 technical publications and holds 4 US patents. Dr. Park served for several technical committees including a member of JEDEC 14-1 Reliability Committee, co-chair of iNEMI Modeling and Simulation TWG, chair of “Electronics Packaging” council in Society of Experimental Mechanics, and an associate editor for ASME Journal of Electronic Packaging. Professor Park has been helping consumer electronics and packaging companies such as Microsoft, Samsung, ASE, Xilinx, and Qualcomm, as a consultant.

Daehan Won, Ph.D., State University of New York at Binghamton, Department of Systems Science and Industrial Engineering

Dr. Daehan Won received a Ph.D. (2016) in industrial and systems engineering from the University of Washington, Seattle, WA. In 2016, he joined the Department of Systems Science and Industrial Engineering, Binghamton University, SUNY, and is currently an assistant professor. His research interests lie in mathematical programming in large-scale programming and data analytics/mining for various healthcare and manufacturing fields. He is recently working on designing new platforms for smart electronics manufacturing system to cope with advances in industry 4.0. He has published thirty-nine journal and conference papers, including Journal on Computing, IEEE CPMT, IEEE Intelligent Systems, etc. Dr. Won’s research has been funded by industry partners such as Koh Young and Analog Devices and national consortium, such as Nano-Bio Manufacturing Consortium. He has been serving as multiple session chairs in international conferences, including the Institute Industrial and Systems Engineers (IISE) and the Institute for Operations Research and the Management Sciences (INFORMS). He received the best paper award in the Data Analysis and Information System track at the 2018 IISE conference. He named the finalist at the SAS data mining paper competition in INFORMS 2016. 

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Published

2021-07-28

How to Cite

He, J., Cen, Y., Li, Y., Park, S., & Won, D. (2021). The Dissimilar Self-Alignment Characteristics of Smaller Passive Components in the Length and Width Directions. Journal of Surface Mount Technology, 34(2), 7–15. https://doi.org/10.37665/smt.v34i2.16