Exploring methods of intelligent development of P&IDs and generation of HAZOP notes

Safety is one of the greatest concerns during projects lifecycles, due to the potential risks and hazards inherent
in their activities. To reach an acceptable level of safety in projects and guarantee a hazard-free work
environment, some structured approaches should be applied. In this respect, Hazard and Operability (HAZOP)
analysis is a systematic process for identifying potential hazards and operability problems in projects. Piping and
Instrumentation Diagrams (P&IDs) serve as the primary input for HAZOP analysis. By using P&IDs, HAZOP
analysis can be beneficial in identifying process deviations, human errors, equipment failures, and other factors
that may lead to any hazardous situation. However, the traditional HAZOP analysis is mostly based on manual
checklists and lengthy brainstorming meetings which make the process slow, error-prone, tedious, and costly. In
this respect, and with the assistance of AI technology, the hazard identification phase can be automated by
automating the information extraction from P&IDs. In the proposed research project, the main focus is on
carrying out a comprehensive literature review and an industry-wide related survey to capture the challenges
and opportunities, and bottlenecks of current methods and investigate potentials of using AI methods to make
the process smart.

Faculty Supervisor:

Osama Moselhi

Student:

Partner:

Hatch Ltd

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Concordia University

Program: