Extended FRAM model based on cellular automaton to clarify complexity of socio-technical systems and improve their safety

Abstract

The safety of socio-technical systems is intractable by traditional approaches, such as a simple cause-effect analysis. It would be no longer effective only to eliminate potential hazards or to explain why things go wrong (i.e., the limitation of the approach called Safety-I). The safety instead could be improved by validating why everyday operations go right and by verifying their resilience, based on an alternative idea of Safety-II. The objective of this research is to develop a tool enabling us to validate and verifying safeties based on the functional resonance analysis method (FRAM). FRAM would be an effective way to analyze the safety of complex socio-technical systems. However, FRAM only provides a conceptual methodology, and further extensions and implementations are needed. This work first presents an extended FRAM model based on a classical idea of cellular automaton, and the result of applying our model to a steel production management problem is provided. Steel production line reveals a quite complicated process consisting of many linked workstations where a production flow might be varied frequently. Wherein flexible delivery decisions are required, including changing the supply chains themselves. There exists empirical know-how to tackle those, but these remain as tacit knowledge, and there has been no way to validate and verify their effectiveness under specific conditions. The results of applying our extended FRAM model to this example provide several insights concerning the characteristics of experienced workers’ operations to handle and manage the process’s complexities, such as harnessing, phase transformation, and identifying critical points attaining resilient operations in terms of the entropy of the process status. We also discuss how these findings contribute to the safety management of the other socio-technical systems based on the findings of the analysis.