GRANTS AND CONTRACTS
Department of Industrial and Management Systems Engineering, Kyung Hee University, Republic of Korea
"Developing a Big Data Analysis Based Recommendation System for Pregnant Weman, Associated With Bundand Cha Medical Center", Korea Technology and Information Promotion Agency for SMEs, August 2015 - July 2016
"Developing Web-based Screening, Coaching, and Referral system for Mental Health Promotion", Ministry of Health & Welfare, September 2015 - December 2015
"Designing products to be maximally differentiated with others and establishing optimal advertising strategies based on cognitive models", National Research Foundation of Korea, November 2014 - April 2016
"Pilot Project on Disaster Management Using Big Data", LX Korea Cadastral Survey Corp., November 2014 - December 2014
"Managing Data Mining Competition", Korean Culture & Tourism Institute, March 2014 - June 2014
"A Study on Building Social Safety Net Using SNS Big Data", Korea Foundation for the Advancement of Science & Creativity, September 2013 - February 2014
"Research on the Countermeasures to Reduce the Occupational Radiation Exposure for Long-term Operated Nuclear Power Plants", Korean Hydro & Nuclear Power Co., Ltd., May 2013 - December 2013
"Advanced Study on Determining the Duplication and Reasonable Price of Research Equipment", National Research Facilities & Equipment Center, October 2013 - December 2013
"Trend Analysis and Quantitative Optimization Evaluation of Nuclear Power Plant Radiation Worker Doses with Using Advanced Statistical Methods", Korean Hydro & Nuclear Power Co., Ltd., September 2012 - August 2013
"Developing and Designing Monitoring Methods of Multiple Changes", National Research Foundation of Korea (NRF), September 2010 - August 2012
"Developing Statistical Process Control Based Health Surveillance Methods", Korea Research Foundation (KRF), May 2009 - May 2010
"A Study on Constructing a Flexible Control Chart for Autocorrelated Data", Korea Research Foundation (KRF), July 2008 - July 2009
"Application of Game Theory to Mobile Communications", Institute for Information Technology Advancement (IITA), April 2008 - March 2011
"Technical Support for the Development of uSPC system", Yongin-si Technical Support Program, October 2007 - September 2008
"Dimensional Statistical Process Control for Low-Volume Production", Kyung Hee University, September 2005 - August 2006



PROJECTS AT TEXAS A&M UNIVERSITY
Department of Industrial Engineering, Texas A&M University, College Station, TX, June 1999 - August 2004.
TITLE: Characterizing and Diagnosing Manufacturing Variation with In-process Measurement Data
SPONSORS: NSF and Texas Advanced Technology Program.
OBJECTIVE: To develop a methodology that, like statistical process control (SPC), aids in understanding and reducing part-to-part variation, but that is tailored to spatially and temporally dense dimensional data.
Development of statistical methods for characterizing the nature of spatial and temporal variation patterns.
Development of interactive computer graphics methods for most effectively visualizing the variation patterns.
Identification and elimination of root causes of manufacturing variability.
Figure 1. Autobody Assembly Process. Graphical Illustration of Spatial Patterns Identified in Quater Panel Subassembly.


Figure 2. Volume (left) and Glyph (right) rendering of a variation pattern that represents bending.
TITLE: Defect Detection and Prevention in Printed Circuit Board Assembly via Information Integration
SPONSORS: Solectron Texas and Texas Advanced Technology Program.
OBJECTIVE: To develop a framework for full utilization and integration of all available Printed Circuit Board (PCB) inspection data from various sources such as X-ray laminography and laser optical inspection machines.
Understanding and characterizing the interrelationship between inspection data from various sensors, defect likelihood, root causes of defects and process degradation, and Printed Circuit Assembly (PCA) reliability.
Development of methodologies for defect and process monitoring with threshold adaptation and root cause diagnostics.
On-line diagnostics and decision making.
Improvement of defect detection and prevention.




                           Figure. Printed Circuit Board (PCB) and Solectorn Texas Logo
TITLE: Statistical Process Control for Low-Volume Composite Manufacturing
SPONSORS: Bell Helicopter Textron Inc.
OBJECTIVE: To develop the framework and guidelines for implementing a statistical process control (SPC) methodology for Quality Assurance (QA) and demonstrate the potential of SPC for improving quality and reducing scrap/rework.
Analysis of airframe assembly process and rotor blade fabrication sequence.
Feature extraction: Identification of Key Product Characteristics (KPCs) and Key Control Characteristics (KCCs) for the processes.
Development of statistical process control (SPC) methodology guidelines.
Development, implementation, and demonstration of pilot statistical process control (SPC) systems.


                            The V-22, Bell Hellicopter Textron Inc.