Product quality development for a corrosion performance prediction software through implementing innovative real-time corrosion data analysis

The developed software product by the qualiTEAS team requires more data to train machine learning-based algorithms. The general objective of this project is to improve the final product of the qualiTEAS team through implementing the innovative design of experiment techniques. The current project will help the qualiTEAS team overcome current challenges and barriers towards improving the final product by characterizing the time-resolved corrosion response.

Faculty Supervisor:

Ali Nasiri

Student:

Partner:

qualiTEAS Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Business Strategy Internship

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