Risk and Reliability Evaluation of Future Industrial Automation Systems: A Systematic Literature Review and Research Agenda

Abstract Today, terms such as sustainable production, industrial cyber-physical systems, cyber-physical production systems (CPPS), software-defined manufacturing, smart manufacturing, Industry 4.0, Industry 5.0, system of systems, internet of things, human-in-the-loop, and digital twins are widely used. These concepts emphasize key characteristics of modern and future production systems, including heterogeneity, structural and behavioral complexity, intelligence, autonomy, reconfigurability, and human centrism. They also highlight the growing importance of reliable and up-to-date risk assessment, safety, and reliability measures, given the significant environmental, economic, and social demands. However, current industrial risk analysis methods lag behind the rising technical sophistication of such systems. It remains unclear whether existing methods can capture complex failure scenarios of dynamic, AI-driven systems with advanced software architectures. This paper presents the main challenges faced by safety engineers in industrial automation and provides a structured classification of risk and reliability analysis methods and metrics, supported by a systematic review of 95 papers up to October 2025. The review addresses questions such as: which CPPS aspects must be considered, which methods are applicable, what are their advantages and limitations, and how can methods be combined? The findings reveal the need to extend classical approaches toward dynamic risk assessment, probabilistic model checking, AI-based techniques, digital twins, and intelligent fault injection. The study provides both a comprehensive overview of current risk and reliability assessment methods for CPPS and a roadmap for advancing their future development.