Towards sustainable Safety 4.0 adoption in manufacturing organizations: enabler modeling and readiness assessment

The adoption of safety measures in Industry 4.0 (I4.0) is emerging as a strategic approach to reduce workplace accidents and improve the safety environment, which has led to the concept of Safety 4.0 (S4.0). With the technological advancements, there exist some new and emerging risks such as cognitive overload, cyber-physical risks, and psychosocial problems. However, the practical implementation of S4.0 remains limited in manufacturing organizations (MOs) due to various resource-related constraints. Hence, it is essential to assess the current level of Safety 4.0 readiness for the successful implementation. The current body of literature in the context of S4.0 related to MOs remains limited compared to I4.0. This study addresses the aforementioned contextual and methodological gaps by developing and analyzing a framework to evaluate S4.0 readiness. At the macro level, the interrelationships and the driving and dependence power of the enablers were identified using Total Interpretive Structural Modelling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis. The key driving enablers are ecosystem and regulatory support, management, and employee readiness. The resulting framework comprises 6 enablers, 28 criteria, and 97 attributes. At the micro level, the readiness of the case organization was evaluated, and the Fuzzy Safety 4.0 Readiness Index (FSRI) was found to be at an average level. Based on ranking scores, 20 of 97 attributes were weaker. The novelty of the study lies in linking micro-level weaker attributes to macro-level driving enablers. This helps MOs to avoid investing resources in highly dependent factors, a common limitation of existing fuzzy logic studies. The study focuses on improvement strategies within the driving enablers.