Analysis of Failure Data and Reliability Assessment for a Sample Gas Turbine at the Shazand Petrochemical Complex

Alikhani, Alireza; Faraji, Alireza; Mirzaei Poinik, Milad

doi:10.22034/IJRRS.2026.9.1.8

Analysis of Failure Data and Reliability Assessment for a Sample Gas Turbine at the Shazand Petrochemical Complex

Document Type : Original Research Article

Authors

Alireza Alikhani

Alireza Faraji

Milad Mirzaei Poinik

Aerospace research Institute, Ministry of Science, Research and Technology, Tehran, Iran

10.22034/IJRRS.2026.9.1.8

Abstract

Reliability of a PG 6541B gas turbine (Unit No. 03) at the Shazand Petrochemical Complex was assessed using time-between-failures (TBF) data collected after the 2019 major overhaul. Thirty uncensored TBF intervals (31 forced-outage events) were recorded over 1692 operating days (June 2020–January 2025). Treating the turbine as a repairable system and adopting a system-level functional renewal (as-good-as-new) approximation, the empirical mean time between failures (MTBF) was 56.40 days (95% confidence interval (CI): 40.63–83.59 days). Comparative distribution fitting (maximum likelihood estimation) selected the two-parameter Weibull model as the best parametric summary of inter-failure times, with shape β = 1.74 (95% CI: 1.32–2.21) and scale η = 1084 days; in this repairable-system context, η is interpreted as the scale of the inter-failure distribution and not as a deterministic lifetime. To address conceptual ambiguity, MTBF is defined as the arithmetic mean of observed TBFs, whereas the Weibull-derived mean inter-failure time (denoted as MTTF in this paper) represents a model-based expectation under the stated renewal-type approximation and can differ substantially in right-skewed small samples. Goodness-of-fit tests (Anderson–Darling and Kolmogorov–Smirnov) supported the adequacy of the selected model. Trend diagnostics showed no statistically significant monotonic trend in the failure process (Kendall τ = −0.097, p = 0.46; Laplace U = 0.761). Sensitivity checks indicated robustness to extreme observations (β changed from 1.74 to 1.68 when the shortest and longest TBFs were excluded). This work contributes an uncertainty-aware industrial case study based on screened long-term field records, providing defensible reliability indicators and interpretation guidance for maintenance planning in petrochemical gas turbines.

Keywords

Repairable system

Time between failures

Weibull distribution

MTBF

Trend diagnostics

Maintenance planning

Subjects

Case Studies Related to Reliability, Risk and Safety

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