Paper on ML-Enabled Geometric Compliance Improvement for Two-Photon Lithography Published in JMP

Our paper titled “Machine-learning-enabled geometric compliance improvement in two-photon lithography without hardware modifications” has been published on Journal of Manufacturing Processes. The paper was co-authored by Yuhang Yang and Prof. Chenhui Shao. In recent years, two-photon lithography (TPL) has emerged as a practical and promising micro- and nano-fabrication technique for a wide range of applications. […]

Paper on Hierarchical Data Models for Additive Manufacturing Published in AM

Our paper titled “Hierarchical data models improve the accuracy of feature level predictions for additively manufactured parts” has been published on Additive Manufacturing. The paper was co-authored by Yuhang Yang and Prof. Chenhui Shao. Industrial-scale production applications of additive manufacturing (AM) are growing rapidly, and scalable AM production requires quality systems that monitor and control […]

Paper on Hybrid Multi-Task Learning-Based Response Surface Modeling Published in JMS

A paper entitled “hybrid multi-task learning-based response surface modeling in manufacturing” is recently published in the Journal of Manufacturing Systems. The paper was co-authored by Yuhang Yang and Chenhui Shao. This paper developed a hybrid multi-task learning-based method tocost-effectively model the response surfaces of multiple similar-but-not-identical manufacturing processes. The method was evaluated using a simulation-based numerical […]

Yuquan’s Work on Multi-Objective Optimization Published in AIMS MBE

Ultrasonic metal welding (UMW) is a solid-state joining method with various industrial applications including battery assembly, automotive body construction, and electronic packaging. Among the advantages of UMW over conventional fusion welding are the ability to join dissimilar metals, reduced energy consumption and short welding time. Despite of its numerous advantages, this technique has a relative […]

Siyuan and Yuquan’s Work on Fault Diagnosis Published in IEEE/ASME Transactions on Mechatronics

Fault diagnosis for rolling elements in rotating machinery persistently receives high research interest due to the said machinery’s prevalence in a broad range of applications. State-of-the-art methods in such setups focus on effective identification of faults that usually involve a single component while rejecting noise from limited sources. This paper studies the data-based diagnosis of […]

Boge and Siyuan’s Work on Human Action Detection and Monitoring Published in Computers in Industry

This paper presents a new approach for temporal detection of short human activities in untrimmed videos. Most present methods for temporal action detection, to our best knowledge, are trained on public action datasets that feature actions spanning up to tens and hundreds of seconds. However, it is often desired in manufacturing, transportation, and other safety-critical […]

Qasim Will Start His Career at MathWorks

Qasim has accepted a Full-Time job offer from MathWorks. He will join MathWorks’s Engineering Development Group (EDG) after his graduation in May 2020. As an application support engineer, he will help customers solve complex technical problems using MATLAB and Simulink. He will also work with various internal teams on software development projects.  His MS research […]

Min-Hsiu Will Start His Internship at iRobot

Min-Hsiu received an internship offer from iRobot and will join iRobot as a Data Science intern in 2020 summer. He will conduct research projects on predictive maintenance of robot vacuums, which is closely related to the field of data science, machine learning, and predictive analytics. The projects are aiming to provide novel solutions for the […]

Prof. Shao Won an NSF CAREER Award

Prof. Chenhui Shao has won an NSF Faculty Early Career Development (CAREER) award for his project “Dynamic Process-Attribute-Data-Performance Modeling to Enable Smart Ultrasonic Metal Welding.” The CAREER Program offers NSF’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances […]

Multiple RA/TA Positions Available to Graduate Students [UPDATE: POSITIONS HAVE BEEN FILLED]

ADM Lab currently has multiple openings for Graduate students. Full scholarships (RA or TA) will be provided. Working on both fundamental methodologies and application-oriented research related to the automation and intelligence of manufacturing, our members are multi-skilled (modeling, simulation, data analytics, hardware, experiment, etc.) We are very proud of our accomplishments over the years as […]