Advances in Hardware Reliability Assessment for Production Systems: A Review of Methods, Developments, Challenges and Future Perspectives

Abstract

Hardware Reliability Assessment HWRA has become essential in modern systems engineering due their increasing complexity. Traditional methods, including Markov models, Bayesian networks, fault tree analysis, reliability block diagrams, Petri nets and FMEA/FMECA, remain fundamental for reliability evaluation. However, Industry 4.0 technologies, including cyber-physical systems, digital twins, industrial IoT and data-driven decision support, expose limitations of conventional approaches. This paper presents a comprehensive critical review of HWRA methods, examining theoretical foundations, modelling capabilities and applications across production systems. It emphasizes dynamic reliability, multi-state systems, mission reliability, hybridization and integration with fuzzy logic, Monte Carlo simulation and data-driven techniques. Unlike previous reviews, it synthesizes the evolution of HWRA toward dynamic, hybrid and AI-enabled frameworks. The literature is analysed through challenges involving uncertainty, scalability, dynamic behaviour, emerging technologies and balance between realism and usability. Remaining gaps include computational burden, expert dependence and limited standardization, motivating future research directions emphasizing HWRA architectures.

Keywords

Hardware reliability assessment / reliability block diagrams / Petri nets / failure mode and effects analysis / fault tree analysis / Bayesian networks / Markov chains/models / dynamic / hybrid / fuzzy logic / Monte Carlo simulation / data-driven / multistate systems / mission reliability

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