Development of optimal joint strategies and an intelligent decision model for lockout/tagout, maintenance and production in a smart manufacturing context

This research project aims to develop a strategic and operational implementation plan for an intelligent approach to integrate safety management processes of production systems in factories. Such safety protocol management is needed for e.g. equipment maintenance operations in manufacturing plants. The involved graduate students will develop novel safety management strategies using Artificial Intelligence, based on available, practical data. Two industrial partners in the field of manufacturing and safety management, Conformit and Cascades respectively, are involved in this study. Intelligent instruction and decision tools for joint safety management, production and maintenance optimization will be developed, implemented and validated using Cascades cardboard and paper plant as testbed. 
The strong involvement of experts at both industrial partners, their vast client portfolio and strategic planning will allow to efficiently transfer the knowledge achieved by this research project to other manufacturing plants across Canada and beyond to increase the safety of workers.

OVERARCHING OBJECTIVE
To develop, validate, and implement an optimal and intelligent strategy (spanning the tactical and operational levels) for safety (environmental health and safety – EHS) management manufacturing systems integrating jointly secure Lockout/Tagout (LOTO) processes to control hazardous energy of production systems with production and maintenance operations using Industry 4.0 technologies, such as Artificial Intelligence (AI) and smart data collection by Internet-of-Things (IoT).

The research project is broken down in different sub-objectives (1 assigned to each involved student), which will be detailed during the interview with interested candidates. The students are integrated within a research team to foster team work.