The Mantua Group

Simple Black and White Asset Management, Reliability Expertise, and Maintenance Execution Perfection.

Weibull

Dealing with Data

Fitness for Purpose, Censoring, and the Discipline of Turning Reliability Data into Reliability Decisions

A reliability engineer who has worked in this field for any length of time has been handed a stack of data and asked to make sense of it. The stack is rarely fit for the question that motivates the engagement. The collection system was usually designed for a different purpose by people in a different function; the records are incomplete in ways that distort the underlying distribution, and the volume of data is sometimes large enough to disguise the absence of useful information. This paper sets out ten principles for working with reliability data well: starting from fitness for purpose, working through the structural problems of censoring and missing renewals, addressing the volume problem with reliability performance indexing, and ending with the most important and most neglected of the ten, talking to the people who collect the data so that the next dataset is better than the last one. The principles are drawn from a Speaking of Reliability conversation between Philip Sage and Fred Schenkelberg and have been translated here into a structured engineering doctrine in the TMG voice.

The Right Tool, at the Right Time, at the Right Depth

Elevating Reliability Engineering Decision-Making Through Disciplined Diagnosis, the Right Tools, Proportionate Method Selection, and Organizational Readiness

Reliability engineering offers no shortage of tools. The discipline has accumulated, across roughly a century of formal practice, an arsenal that includes Weibull life-data analysis, fault tree analysis, FMEA and FMECA, root cause analysis, control charts, modal analysis, design of experiments, accelerated life testing, condition monitoring, reliability-centred maintenance, and dozens of variants. The persistent failure mode in the field is not a shortage of tools but a mismatch between the tool and the problem: an over-engineered analysis applied to a question a five-minute hypothesis test would have settled, or a sophisticated technique deployed in an organisation that has not yet developed the foundational disciplines required to absorb its output.

Statistical Rigour in the Regulatory Arena: Weibull Analysis Certification and the Victorian AER REPEX Challenge

How independent Weibull MLE certification, aligned with the AER’s 2024 Asset Replacement Planning guidance, contributed to the evidentiary strength of regulatory proposals across Victorian electricity distribution network submissions.

Victorian electricity network service providers are engaged in one of the most consequential regulatory processes in recent memory. The Australian Energy Regulator (AER) has reviewed the combined revenue and capital expenditure proposals of five Victorian distributors, AusNet Services, Jemena, Citipower, Powercor, and United Energy, for the five-year regulatory control period commencing 2026.

The AER’s draft determination trimmed the distributors’ collective capex claims by approximately $3.7 billion, with the contested quantum approaching $2.9 billion once the revised proposals were filed. Central to the regulatory debate is the quality and defensibility of probabilistic asset replacement expenditure (REPEX) modelling, and, in particular, the statistical validity of the Weibull-based Probability of Failure (PoF) functions that underpin each distributor’s replacement case.

The Mantua Group (TMG) provided independent Weibull Analysis certification and expert advisory services to selected network service providers engaged in this regulatory process. Our work, conducted in alignment with the AER’s 2024 Asset Replacement Planning (ARP) Practice Note and the AER REPEX Model Framework, strengthened the statistical foundation of REPEX submissions across key asset classes, including distribution transformers, substation power transformers, and overhead conductors. This white paper describes the regulatory context, the methodology we applied, and the outcomes attributable to TMG’s involvement.

Weibull Statistical Analysis for Transmission Asset Reliability

Applying Weibull for Maximum Likelihood Estimation to Left-Truncated and Right-Censored Lifetime Data

This white paper presents a rigorous statistical methodology for analyzing transmission line asset reliability using Weibull distribution analysis. The approach specifically addresses the analytical challenges inherent in utility asset data: left-truncated observations from legacy system migrations and informatively right-censored data from inspection-driven replacement programs.

A study of approximately 15,000 transmission structures across an 11,000-kilometer network demonstrates the Weibull methodology’s practical application. By employing Maximum Likelihood Estimation (MLE) rather than ordinary least squares regression, the analysis produces unbiased parameter estimates even under complex censoring conditions that would render traditional approaches unreliable.

Key findings reveal that unique classification of assets exhibit similar but different reliability characteristics, with characteristic lives (η) of 60 and 75 years, respectively, and shape parameters (β) indicating wear-out failure modes in both populations.

Wood Decay Engineering for Transmission Pole Assessment

Applying AS 1170.5 Draft Wood Decay Modeling to Predict Functional and Catastrophic Failure Thresholds

This white paper presents an engineering methodology for predicting wood pole deterioration using decay progression models aligned with AS 1170.5 Draft, the Australian standard. The approach integrates field-measured decay rates from test stake programs with pole geometry to establish both functional failure (FF) and catastrophic failure (CF) thresholds for transmission structures.

A critical finding is that failure timing is highly dependent on original pole diameter, not simply pole age. Analysis demonstrates that functional failure for minimum-diameter poles may occur 50 years before maximum-diameter poles of the same age and treatment cohort, fundamentally changing how asset managers should prioritize inspections and replacements.

The methodology incorporates treatment effects for both Pressure Impregnated (PI) and Natural Round (NR) timber, accounting for preservative type, retention levels, and the progression of wood decay through sapwood, outer heartwood, and inner heartwood (corewood) zones.