Multivariable Industrial Alarm Monitoring and Management

This project aims to develop, evaluate, and apply advanced solutions and techniques for assisting industrial plant operators in decision-making during abnormal situations, thereby improving plant safety and reliability. Currently, plant operators receive too many alarms, making it difficult to respond effectively. In industrial facilities, developing strategies for sustainable Environmental, Health, and Safety (EH&S) performance and corporate social responsibility is increasingly important. Achieving EH&S targets can yield significant economic benefits by preventing costly unplanned shutdowns, equipment damage, and operation failures. To ensure quality, efficiency, and EH&S performance, it is crucial that operators are promptly informed of faults and abnormal situations via the alarm system, allowing for timely and appropriate responses. Our goal is to analyze the alarm data and develop advanced solutions to reduce unnecessary alarms and improve the overall alarm system performance. By using data from existing systems, we will identify patterns and causes of alarm floods and create tools to help operators manage these situations better. This project will involve close collaboration with industry experts and use real industrial data to ensure practical and effective results. Ultimately, the improved alarm systems will enhance plant safety, reliability, and environmental compliance, benefiting the partner organization and the wider Canadian industrial sector

Faculty Supervisor:

Tongwen Chen

Student:

Partner:

Parkland Burnaby Refinery

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Alberta

Program: