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Intelligent Anomaly Synthesizer


Term:

IAP

Department:

2: Mechanical Engineering

Faculty Supervisor:

Kamal Youcef-Toumi

Faculty email:

youcef@mit.edu

Apply by:

Jan 31 2021

Contact:

Steven Yip Fun Yeung: yyeung@mit.edu

Project Description

Mechatronics Research Lab (MRL) is looking for UROP candidates with strong skills and/or interest in a) Software development (particularly with Python and Matlab) and b) IoT-based hardware design and instrumentation. This project aims to give us insights on intelligent diagnostics and prognostic of various industrial manufacturing systems.

Pre-requisites

The software development candidate will focus on multiple software aspects of the project. The primary focus will be on optimizing the data acquisition pipeline from an intelligent mechatronics setup. Existing scripts are allocated in multiple microcontrollers and sensor units, the goal is to integrate separated pieces into a centralized program, most preferably in a Matlab package. This part of the project will require a significant amount of practice in system design and actual mechatronics implementation. Furthermore, the other task is to build and publish a preliminary ‘cloud’ website for researchers to access the intelligent set up and conduct experiments remotely, and to publicize the data sets obtained from the setup locally. The hardware development candidate will focus on the hardware improvement of the current intelligent hardware. This will involve much engineering analysis and prototyping practice. The UROP also have the chance to extend the functions of the current setup with his/her own designs, both in the mechanical domain and in the electrical/electronic domain. The project is a very good chance to organize and publish our own datasets for anomaly detection of physical machines, which is a very contributing work in the field. Candidates have good opportunities for publications and patents during the research. UROP candidates are expected to gain various technical knowledge & skills in different domains such as mechanical engineering, machine learning, system design, and electrical sensors with projection on real industrial applications. This role involves regular communication meetings with project members and the principal investigator on progress and risks.