Dynamic Reliability Analysis of Rotary Atomizer Spray Dryers: A Hybrid Fault Tree and Markov Approach for Risk‐Informed Maintenance

This paper presents a quantitative reliability analysis of a rotary atomizer spray‐drying line, used here as a representative application of complex rotating process equipment. A Static Fault Tree (SFT) Analysis models four primary failure modes: mechanical degradation, tower over‐temperature, feed loss with missed cleaning and undetected airflow loss. The analysis is extended to a Dynamic Fault Tree (DFT) framework that captures temporal ordering, standby behaviour and demand‐dependent failures through dynamic gates, and is quantitatively evaluated via a hierarchical Continuous‐Time Markov Chain (CTMC) approach. The integration of DFTs and CTMCs is a mature research stream; however, fewer studies show how to apply a selective DFT–CTMC refinement to industrial process equipment while preserving fault‐tree interpretability for engineering decision making. The contribution of this work specifically lies in using a targeted SFT–DFT–CTMC refinement strategy in which only the branches whose physical behaviour requires temporal or demand‐dependent modelling are converted into local Markov modules, while the upper‐level fault‐tree structure remains readable and reusable for maintenance prioritisation. Based on this framework, two mission time horizons are examined: a short‐term period representing operational campaigns between cleaning‐in‐place cycles and a long‐term period representative of the atomizer's operational lifetime. Results show that the SFT provides a conservative upper bound, overestimating the top‐event probability by approximately 40%–70% relative to the DFT, with potential distortion of importance rankings. By filtering dynamically implausible sequences, the DFT–CTMC model emphasises protection and diagnostic subsystems and supports risk‐informed design and maintenance priorities through time‐dependent importance (Fussell–Vesely) and sensitivity analyses. The proposed hybrid hierarchical workflow is transferable to other rotating process assets featuring protection chains and demand‐driven actions.