AI Nétur

This project deals with the development of three applications of Artificial Intelligence and Operations Research aiming at improving the cost, response time and flexibility of production cost assessment, process planning and production at Nétur. Nétur manufactures high precision parts for Original Equipment Manufacturers (OEM) in the aerospace industry, such as Pratt & Whitney. Data mining and machine learning techniques will be adapted and implemented to support both production cost assessment and process planning. Computer vision will be used to automatically recognize alphanumerical characters and symbols, and design features from 2D engineering drawings. This data, along with known process plans from Nétur, will be used to train models to predict complete or partial process plans from design features. In order to include the human process planner in the loop, this project will adopt an interactive planning system design approach to develop an interactive computer-aided process planning system. Finally, this project will exploit operations research to develop an advanced scheduling tool capable of taking advantage of tool similarities and standardization between jobs, as well as multiple process plans per part. This project will be supervised by 6 professors from Polytechnique Montréal with expertise in manufacturing, machine learning, computer vision and operations research.

Faculty Supervisor:

Jean-Marc Frayret;Guillaume-Alexandre Bilodeau;Christophe Danjou;Michel Gamache;Bruno Agard;Richard Labib;Guillaume-Alexandre Bilodeau

Student:

Partner:

Netur Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

École Polytechnique de Montréal; Polytechnique Montréal

Program: