Avaliação de indicadores de segurança em indústrias de alto risco no contexto da engenharia de resiliência: uma revisão sistemática da literatura

Abstract

Measuring safety performance has been a challenge for the management of productive organizations, particularly in the traditional context of Safety Engineering. As a response to this challenge, Resilience Engineering emerged as an alternative model, especially regarding early warning and response to large-scale accidents caused by organizations that deal with high technological risk. This study aims to discuss and analyze qualitative and quantitative methods to identify the potential for resilience in safety management and support new research on resilience engineering applied to safety performance management in industries with high technological risks. This is a systematic literature review study over the last ten years, starting in 2012. The results provided a critical analysis of the selected methods that pointed out potential Resilience Indicators in safety management in organizations defined as Complex Sociotechnical Systems. Qualitative methods indicated a better path for highly complex organizations than linear analytical models, as one of their disadvantages is the difficulty in assessing the resilience of organizations, as it is a multidimensional phenomenon. It was found that few selected quantitative studies aimed to systemically measure the four main dimensions of resilience in organizations (anticipation, response, monitoring, and learning). As a limitation of the research, there is a possible loss of information that may occur due to studies excluded from the literature review. Another difficulty concerns the diversity of definitions of resilience and Resilience Engineering, without there being a consensus, especially because it is a relatively new area and involves a multidisciplinary view of processes and studies that use different analytical methods and instruments. It is expected to contribute to the advancement of knowledge in safety management in organizations with high technological risk. It is recommended for future studies to analyze successful practices to anticipate incidents or recover operational normality after their occurrence, considering the resilience capacity of Complex Sociotechnical Systems.