Purpose This paper aims to enhance the reliability of steam turbine systems in sulfur recovery units (SRUs) within the gas processing industry. These turbines are essential for driving air blower systems in the Claus process, yet they frequently encounter reliability challenges such as high vibration, misalignment and component degradation. The paper seeks to identify critical failure points and propose a robust improvement strategy. Design/methodology/approach A quantitative reliability framework is applied using ten years of historical maintenance data. Component failure behavior is modeled using an exponential failure distribution. System reliability is evaluated through reliability block diagram (RBD) modeling for series–parallel configurations, while availability is assessed using MTBF and MTTR metrics. A quantitative risk-based criticality index combining failure rate and repair duration is employed to prioritize failure-prone subsystems and guide reliability improvement efforts. Findings The results identify the steam turbine (ST), air blower (AB), overspeed mechanical trip mechanism (OMM) and coupling (CT) as the most critical components impacting system reliability. The proposed optimized reliability model achieves system availability of 99%, contributing to enhancing operational continuity, reducing maintenance costs and improving overall system safety. Originality/value This research provides a novel, component-level reliability assessment model for SRU steam turbines. It offers practical guidance for improving turbine performance and supports broader industry efforts toward predictive maintenance and operational excellence by integrating risk-based prioritization and reliability metrics.
Mohammed et al. (Mon,) studied this question.