AI-PHM (Advisor: Prof. Daeil Kwon) webpage has been moved to http://phm.skku.edu
Welcome to AI-PHM Lab
About AI-PHM Lab
AI-PHM lab at SKKU is dedicated to developing and implementing core technologies to assess the reliability of engineering assets and to predict their future reliability using PHM (Prognostics and Health Management). We focus on developing smart IoT sensors to self-diagnose faults in real-time, improving the availability and reliability of engineering assets, covering from semiconductor electronic packages to manufacturing equipment. We also study 3D printed parts and products to enhance their quality and reliability in the field. We are currently working with universities, industries, research institutions, as well as government agencies
Research interests
Partners
Funded Projects
(2018-2018) Development of 3D Printing-based Smart Manufacturing Core Technologies based on 3D Printing, co-PI, Ulsan city
(2017-2019) Deep Learning based Fault Diagnosis of Equipment in Coal Fired Boilers, co-PI, East West Power
(2017-2020) Detection of Interconnect Fault of Electronic Packages Based on Artificial Intelligence, PI, NRF
(2016-2017) Development of Core Technologies for Fault Prognostics and Management of Smart Manufacturing Systems, PI, KEIT
(2016-2017) Development of Noise Analysis Algorithms Based on Machine Learning, co-PI, Samsung Electronics
(2015-2020) 3D Printing Infrastructure Construction for Eco-Friendly Automotive Parts Research and Business Development, co-PI, KEIT
(2015) Big Data Cloud Service for Manufacturing Process Analysis, co-PI, HHI
(2015) Reliability Assessment of Low-Power Process Based Supercomputers, PI, KISTI
(2014-2019) System Reliability Improvement and Validation for New Growth Power Industry Equipment, PI
(2014-2017) Development of Electronics Health Management System based on High Speed Signal Analysis, PI, NRF
(2014-2017) Development of Life Prediction System for Electronics Using Digital Communication Signal, PI, UNIST
(2013-2019) Strategic Program of Interdisciplinary Human and Systems Engineering for Technologically Driven Human-Centered Factories of the Future, co-PI, BK21+