Digital Twin-Based Factory
Co-Principal Investigator
Dr. Zahra Sotoudeh
Dr. Zahra Sotoudeh’s areas of expertise are computational structural dynamics (CSD) and aeroelasticity, and statistical energy analysis. Zahra joined aerospace engineering department in Fall 2016. Zahra is an associate fellow of AIAA. Dr. Sotoudeh is one of the Co-PIs for the CREST-RASM grant.
Subproject 1
IME Smart Manufacturing Lab’s Intelligent Factory: A Novel Paradigm for Enhanced Operations, Predictability, and Safety
Overview
Despite the growing body of literature on digital twins in smart manufacturing, most studies primarily focus on simulation with either no data exchange or only a one-way flow of data from physical assets to their digital counterparts. To the best of our knowledge, only a few research studies have focused on creating a true digital twin for a factory. A true digital twin is capable of bidirectional data exchange, where the digital replica not only reflects real-time updates and predictions from physical assets but also sends actionable commands back to the physical factory.
Goal
The goal of Subproject 1 is to create an Intelligent Factory (IF), which involves physical assets and their digital replica with bidirectional data exchange.
The proposed structure has three layers, which are the subject of this subproject research:
- Manufacturing stations and their digital replica
- An embedded AI
- An intricate bidirectional data flow between physical stations, their digital counter-parts, and the embedded AI
Outcome
The research outcome will provide a methodology and framework for developing a bidirectional digital twin of factories, which can be adapted by different types of manufacturing processes or other engineering applications.
Research Faculty and Staff
