Safety Modeling in an Automated Production Environment Using KPIs

Abstract With the increasing automation of production processes, there is a growing need for systematic monitoring of the safety and effectiveness of operational activities, which requires the use of appropriate performance indicators. The aim of the study was to develop a model for identifying key performance indicators (KPIs) for production and operational safety in an automated manufacturing environment. The research was based on a review of scientific literature, surveys, and nominal meetings with industrial safety experts. The identified KPIs were divided into three groups: preventive, monitoring, and result indicators. This approach enables multifaceted analyses covering preventive measures, ongoing monitoring, and evaluation of the effectiveness of implemented countermeasures. The proposed solution contributes to increasing employee safety, machine reliability, and the continuity of the entire enterprise. The verification of the proposed model confirmed its usefulness and practical applicability. The developed model can provide practical support for production engineers, safety specialists, and those responsible for system development in industrial organizations. Future research may focus on enriching the model with predictive solutions using advanced data analytics and machine learning methods.