IMS to Organize Invited Session at AMEST 2022

The IMS Center will be organizing an invited session at the upcoming Advanced Maintenance Engineering, Services and Technology (AMEST). This event will take place beginning Tuesday, July 26, 2022 through Friday, July 29, 2022. This session will be hosted by Dr. Jay Lee, Dr. Marco Macchi (Politecnico di Milano), Dr. Laura Cattaneo (LIUC - Università Cattaneo), and Dr. Xiaodong Jia and will focus on Data Quality Issues in AI-enabled Maintenance Systems.

For more information about this invited session, please see the abstract below.

Session Overview

AI-enabled maintenance systems are a key area where Industrial AI is today promising high expectations for the coming years. To guarantee those expectations are met in the industrial context, a systematic discipline is required. The purpose is to quickly develop, validate and deploy machine learning algorithms for sustainable performance across different applications. It leads to implement AI-enabled maintenance systems that allow consistent performance across industrial assets. This systematic discipline should address common issues experienced in AI problems, including data quality, features engineering, algorithms selection, and platform integration. Data quality is a cornerstone on top of which to build effective supervised/unsupervised and transfer learning algorithms. In many applications, it is difficult to obtain a large and comprehensive training dataset, and the quality of data labeling is heavily dependent on the human experience and ability. Currently, there is no holistic approach to integrating data, AI, and the tasks performed by the model.

The deadline to submit a paper to this AMEST session is December 19, 2021. To learn more about this event and to see full registration details, please visit the AMEST 2022 website here.


Featured in this Article
Professor Jay Lee
Dr. Marco Macchi
Dr. Laura Cattaneo
Dr. Xiaodong Jia