Automated safety-in-design rule-checking for capital facility projects

Safety-in-design (SID) reviews are mandatory for capital facility projects because they eliminate hazards before activities in the construction, operation, and maintenance phases take place. Existing SID review processes which many large corporations have in place, however, still rely mainly on manual input and judgment of experienced safety experts. Often very skilled humans make decisions based upon paper-based drawings or three-dimensional visualization models. As such, tasks in safety-in-design review sessions remain to be manual and thus are very much time-consuming, expensive. Furthermore, if not all hazards are detected and mitigated, they can be potentially error-prone. Unsafe design ultimately exposes workers at risk as it provides an unsafe work environment. It can also become very costly if unsafe design is detected outside of the design and construction planning phases of a capital facility project. The objective of this work was to develop a safety code compliance checking technology that does not replace human judgment, but supports human decision making of safety experts, designers, engineers, and field staff. The developed work applies novel safety code compliance checking algorithms on intelligent information models which are prepared during design and construction planning. The initial scope of the developed algorithms is limited to check for safe work access and egress requirements in existing information models. As existing safety rules and best practices are embedded in the developed code compliance checking system, they can be automatically executed on information models which exist for every capital facility project. A case study is presented to illustrate its practical implementation for an off-shore oil platform. Results show that the developed system generates automated reports that list the safety violations and furthermore, along with visual screenshots of the unsafe object in the information model, indicate the process of how these issues can be mitigated based upon established best safety practices. The significance of human-assisted decision-making in SID reviews and its potential to lead to safer designs early in a project is explained.