Maquettes numériques comme outil de prévention et d’aide à la décision en santé et en sécurité du travail

Abstract

Digital mock-ups promote the observation of future work situations through the geometric representation of products/facilities. They can be coupled with knowledge management technologies to identify occupational health and safety (OHS) risks in the design stage. Risks of this type are major risks that present themselves during the operation and maintenance stages of industrial facilities. Therefore, coupling digital mock-ups with knowledge management technologies is one approach that can be taken to prevent at the source risks that are present in the operation and maintenance stages of industrial facilities. Moreover, this approach makes it possible to combine the visualisation benefit digital mock-ups offer with the rigour of formal structured risk identification methods, such as fault tree analysis, job hazard analysis, hazard and operability analysis (HAZOP), and checklists. Checklists in particular make it possible to ensure the products/facilities comply with applicable OHS regulations. In this study, we carried out a comparative analysis of OHS risk management approaches using Building Information Modelling (BIM) and Product Lifecycle Management (PLM) digital mock-ups. Our analysis revealed that automatic model checking tools, which are available in both BIM and PLM modelling environments, are suitable for automatically checking products/facilities comply with OHS regulations. Since Catia V5 is the software program our industrial partner’s designers use, we studied the automatic model checking tools available in Catia V5. We used design science research principles for this task. We then proposed a risk identification approach that involves using macro codes in Catia V5 to record the OHS rules the products/facilities must comply with. However, these rules must first be: 1) extracted from an industrial facility’s maintainability and operability requirements guides (MORGs), 2) suitably reformulated so they are compatible with the RASE method, and 3) interpreted into a machine-readable language using the RASE method. We used a case study of a water spillway belonging to our industrial partner to analyse the feasibility of our proposed approach. Since risks linked to energy sources appeared to be our industrial partner’s highest-priority risks in the operation and maintenance stages of its facility, the case study consisted of trying to use our proposed approach to automatically identify energy sources in the digital mock-up. The case study made it possible to identify two main difficulties when it comes to operationalising the proposed approach—1) the need to standardise the nomenclature of digital objects and design procedures, and 2) the need to reserve colours to signal the level of risk digitally represented objects pose for workers’ health and safety. However, the case study also enabled us to validate the feasibility of the proposed approach and, thus, the possibility of using digital mock ups to eliminate at the source regulated risks associated with the operation and maintenance stages of industrial facilities. Moreover, the proposed approach has three limitations: 1) it fails to take into account the effects of interactions and reinforcement links between risks, 2) it cannot anticipate situations that are not foreseen in MORGs, and 3) it fails to integrate human factors related to interactions between humans and products/facilities during critical maintenance’s tasks. To this end, we propose to study in future work the possibility of coupling digital mock-ups with emerging risk identification methods such as the Functional Resonance Analysis Method (FRAM) or the System Theoretic Accident Model and Process (STAMP/STPA) to be able to identify the risks associated with situations that are not foreseen in MORGs and the effects of reinforcement links between risks. Finally, we propose to study the possibility of using Catia V5’s ergonomic analysis module to integrate human factors engineering / ergonomics in facility design and thus help to reduce the frequency of occurrence of ergonomic risks that are particularly liable to generate musculoskeletal disorders among workers in the operation stage of industrial facilities.

Date	12 Sept 2022
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Sylvie Nadeau (Supervisor), Conrad Boton (Co-supervisor) & Louis Rivest (Co-supervisor)