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Progress in Field Reliability?

by Larry George Leave a Comment

Forecast Parts’ Demands, Without Life Data, for a Nonstationary Process

Forecast Parts’ Demands, Without Life Data, for a Nonstationary Process

In the 1960s, my ex-wife’s father set safety stock levels and order quantities for Pep Boys. He used part sales rates and the Wilson square-root formula to set order quantities. 

Why not use the ages of the cars into which those parts go, to forecast part sales and recommend stock levels? Imagine you had vehicle counts (year, make, model, and engine) in the neighborhoods of parts stores, catalogs of which parts and how many go into which cars, and store sales by part number.

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George Leave a Comment

Dependence in Production Lines

Dependence in Production Lines
golden oil burning lamp (Genie's home)

As I rode, I thought, how could I use reliability statistics to optimize a solar-tube production line? Then I noticed a brass glint in the scrub brush. It didn’t look like trash, so I stopped and found an old brass oil lamp like Aladdin’s. Naturally, I rubbed it. There was a flash and a puff of smoke, and out popped the genie who said, “Yes master, by the powers vested in me, I grant you three wishes.” 

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 1 Comment

Reliability Estimation With Life Limits but Without Life Data

Reliability Estimation With Life Limits but Without Life Data

Would you like age-specific field reliability of your products and their service parts? Age-specific field reliability is useful for reliability prediction, diagnoses, forecasting, warranty reserves, spares stock levels, warranty extensions, and recalls. Nonparametric estimation of age-specific field reliability is easy, if you track parts or products by name and serial number for life data. What if there are life limits? What if there’s no life data?

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 1 Comment

Subjective Fragility Function Estimation

Subjective Fragility Function Estimation

I needed multivariate fragility functions for seismic risk analysis of nuclear power plants. I didn’t have any test data, so Lawrence Livermore Lab paid “experts” for their opinions! I set up the questionnaires, asked for percentiles, salted the sample to check for bias, asked for percentiles of conditional fragility functions to estimate correlations, and fixed pairwise correlations to make legitimate multivariate correlation matrixes. Subjective percentiles provide more distribution information than parameter or distribution assumptions, RPNs, ABCD, high-medium-low, or RCM risk classifications.

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George Leave a Comment

Credible Reliability Test Planning

Credible Reliability Test Planning

How to allocate subsystems’ MTBF requirements with testing? Name-withheld-to-protect-the- guilty proposed “Top-Down” reduction in subsystem MTBF requirements; the more subsystems (in series) that you test, the lower the subsystem required MTBF! “The correct formula is

1/MTBF(subsystem requirement) = 1/MTBF(system requirement) –
((# of subsystems in series – # of subsystems tested)/MTBF(subsystem).”

This “Top-Down…” method is uncited and not found in Internet search. 

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 1 Comment

Why Kill Controls?

Why Kill Controls?

“The effects of chance are the most accurately calculable, and the least doubtful of all factors in the evolutionary situation.”

R. A. Fisher, ca. 1953

COVID-19 vaccination claims have changed from “prevention” to “reduced severity.” FDA approved Pfizer’s vaccine for 95% efficacy, compared with the placebo control sample. Pfizer’s placebo sample had 86% efficacy, compared with the US population case rate! Sample subjects resembled each other but not the US population! 

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 1 Comment

Please Enter Forecast_____

Please Enter Forecast_____

Reliability-based forecasts can be made from field data on complaints, failures, repairs, age-replacements (life limits), NTFs (no trouble found), WEAP (warranty expiration anticipation phenomenon), spares, warranty claims, or deaths. Some spares inventory forecasting software says… “Please enter forecast______” No kidding. 1800 years ago Roman Jurist Ulpian made actuarial pension cost forecasts for retiring Roman Legionnaires. Would you like actuarial forecasts? Their distributions? Stock recommendations?

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 2 Comments

What Price Required Data?

What Price Required Data?

The title was inspired by Rupert Miller’s report “What Price Kaplan Meier?” That report compares nonparametric vs. parametric reliability estimators from censored age-at-failure data. This article compares alternative, nonparametric estimators from different data: grouped, censored age-at-failure data vs. population ships and returns data required by generally accepted accounting principles. This article compares data storage and collection requirements and costs, and bias, precision, and information of nonparametric reliability estimators. 

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 1 Comment

Why didn’t you ask before running all those tests?

Why didn’t you ask before running all those tests?

The title is a Statistician’s Lament. “Design of Experiments (DoE) is the design of any task that aims to describe or explain the variation of information under conditions that are hypothesized to reflect the variation.” [Wikipedia] Are you using DoE to design reliability tests? What do PH, GMDH, and |D|-optimality have to do with design of DoE of reliability tests?

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George Leave a Comment

Origin-Destination Matrix and Travel Time Distribution Estimation, Without Survey Data

Origin-Destination Matrix and Travel Time Distribution Estimation, Without Survey Data

Bob Butler nuclear engineer, musician (www.pleasantonband.org), former city councilman and Mayor of Pleasanton, California  died October fifth https://www.pleasantonweekly.com/news/2021/10/14/what-a-week-remembering-bob-butler-former-pleasanton-mayor-and-councilman. He helped me get traffic counts data from the Pleasanton Traffic Department.

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 4 Comments

Error in Inspection Time Interval

Error in Inspection Time Interval

IEC 60601-1 says… Estimate the probability per time pe of an electrical failure and of an oxygen leak po. Determine the accepted probability of dangerous failures [fire] per time r. Calculate the inspection time interval tc = r/(0.5*pe*po).

A friend asked, “What’s the 0.5 for? It doesn’t account for the fire event sequence: leak before spark.” I posted correction tc = r/((po/(po+pe))*pe*po) and notified the IEC committee which acknowledged, “We’ll consider your suggestion for edition 4.”

[An earlier, shorter version of this article on www.LinkedIn.com, July 5, 2018. This version describes an inspection-time and risk-analysis template.]

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 1 Comment

What to do with Obsolescent Nuclear Engineers?

What to do with Obsolescent Nuclear Engineers?

When nuclear power plants were built, companies had quality assurance programs and US Nuclear Regulatory Commission risk standards. Now the nuclear industry faces obsolescence. Qualifying replacement parts and replacing analog instrumentation and controls with digital systems generates some reliability testing work. NASA solicits unmanned nuclear power plants on the moon and Mars. Nevertheless, the demand for nuclear engineers is decreasing. Fortunately, the nuclear industry spawned risk analyses useful in other industries. 

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George Leave a Comment

Bivariate Reliability Estimates from Survey Data

Bivariate Reliability Estimates from Survey Data

Isn’t it enough to estimate the age-specific field reliability functions for each of our products and their service parts? Of course we quantify uncertainties in estimates: sample uncertainties and population uncertainties due to changes or evolution. That’s information to forecast service requirements, recommend spares, optimize diagnostics, plan maintenance, warranty reserves, recalls, etc. What else could we possibly need or do?

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George Leave a Comment

Help! They Lost the Data

Help! They Lost the Data

What can we do without reliability function estimates? FMEA? FTA? RCA? RCM? Argue about MTBFs and availability? Weibull? Keep a low profile? Run Admirals’ tests? Look for a new, well-funded project far from the deliverable stage? 

Ask for field data; there should be enough to estimate reliability and make reliability-based decisions, even if some data are missing. Field data might even be population data!

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

by Larry George 1 Comment

Estimation of a Hidden Service-Time Distribution of an M(t)/G/∞ Self-Service System

Estimation of a Hidden Service-Time Distribution of an M(t)/G/∞ Self-Service System

(This is chapter 5 of User Manual for Credible Reliability Prediction – Field Reliability (google.com), cleaned up and typeset for AccendoReliaiblity Weekly Update.) 

The nonparametric maximum likelihood estimator for an M/G/∞ self-service time distribution function G(t) extends to nonstationary, time-dependent, Poisson arrival process M(t)/G/∞ systems, under a condition. A linearly increasing Poisson rate function satisfies the condition. The estimator of 1-G(t) is a reliability function estimate, from population ships and returns data required by generally accepted accounting principles. 

[Read more…]

Filed Under: Articles, on Tools & Techniques, Progress in Field Reliability?

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