ESS is a process designed to force latent defects to reveal themselves. It does this by applying controlled environmental stresses to hardware, accelerating the transition from hidden weakness to detectable failure.

The goal is not to test whether a product meets specifications. The goal is to flush out defects that already exist but have not yet developed into failures under normal conditions.

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by Michael Keer Leave a Comment

Hardware Product Realization in the Age of AI

Chapter 4: Difference between Agile Hardware and Agile Software

In the previous chapter, how markets and global needs can impact your product was discussed.

In this chapter the differences between agile Hardware and Agile Software are explored to allow you understand how to apply agile techniques to a hardware development workflow.

The desire to gain a competitive advantage by releasing products faster has driven the widespread adoption of agile software methodologies. More recently, a push to apply agile techniques into the hardware development process has yielded mixed results, This is because electronic hardware products cannot be tested until complete subassemblies are built, and so important modifications to the product realization process are necessary.

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by Larry George Leave a Comment

The Field Reliability Applications Award

From ASQ Reliability Review, Vol. 16, No. 3, Oct. 1996. Revised 2002, 2018, and Jan. 4, 2026.

The Apple Computer Reliability Department manager, Wayne Smith, told me (circa 1991), “We make sure Apple doesn’t sell a product that doesn’t work,” (by in-house product tests during design phase). (I worked in Apple’s Service Department.) Testing helps, but real, age-specific reliability is determined in the field, in the hands of customers, in their environments. Companies could benefit from using age-specific, field reliability to eliminate waste, improve customer satisfaction, and reduce uncertainty. The Field Reliability Applications Award is a clone of the Malcolm Baldrige National Quality Award modified to quantify reliability maturity. The field reliability applications evaluation in this article supplements Fred’s podcast on “Reliability Maturity” [Schenkelberg].

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by Hemant Urdhwareshe Leave a Comment

Introduction to JASP: an Open Source Free Statistical Software

Dear friends, wish you all a very happy 2026! After a long gap, I am happy to release my 104th video! As we all know, statistical analysis software is becoming quite expensive to buy and maintain! On this background, it is good to know that there is a powerful open-source statistical analysis software ‘JASP’ which is completely free! While JASP is free, its capabilities are excellent and can be a good substitute for a commercial software! I thought of sharing some information about this free open-source software JASP! In future, I intend to demonstrate how to use JASP for performing statistical analyses in few more videos. Your feedback is welcome!

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by Ray Harkins Leave a Comment

Statistical Robustness

Why “Good Enough” Assumptions Often Are

Co-authored with Mike Vella

If you’ve spent any time working with real manufacturing, reliability, or field data, you already know an uncomfortable truth:

Most statistical models assume ideal conditions that rarely exist in practice.

Textbooks often begin with assumptions like perfectly normal distributions, clean random samples, and well-behaved processes. Meanwhile, engineers are dealing with skewed cycle times, mixed populations, censored failure data, process shifts, and the occasional mystery outlier that refuses to explain itself.

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by Michael Keer Leave a Comment

Hardware Product Realization in the Age of AI

Chapter 3: Understanding your Markets

In the previous chapter, the Product Realization will be defined at a high level as well as the ideas behind a New Product Development Introduction (sometimes written as NPDI) framework.

In this chapter the effects of the market on your product are discussed, what you think is the best version of your idea may be influenced by many factors in the markets you believe you can sell it to.

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by Hemant Urdhwareshe Leave a Comment

Reliability Prediction with Monte Carlo Simulation with Free Software

Dear friends, we are happy to release this 104th technical video. In this video, Hemant Urdhwareshe explains and illustrates use of Monte Carlo Simulation to predict reliability using an open-source free software Argo. Hemant Urdhwareshe is a Fellow of ASQ and is certified by ASQ as CRE, Six Sigma Master Black Belt, CQE and CMQ/OE.

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by Carl S. Carlson Leave a Comment

Quality Objective 11: ADDRESS HIGH-RISK FAILURES

“In the middle of difficulty lies opportunity.” Albert Einstein

There is no more important outcome from an FMEA than identifying and addressing high-risk issues. In this article, I will outline how to evaluate an FMEA against the FMEA Quality Objective for addressing high-risk failures.

What is meant by “address high-risk failures”?

The level of risk in an FMEA is identified in the Risk Priority column. For each failure mode and corresponding effect and cause, the FMEA team designates the level of risk, such as “high” or “medium” or “low.” High-risk failures are those that the FMEA teams assigns the highest level of risk, based on appropriate FMEA standard or company policy.

“Address” means “to deal with, handle, or give attention to a problem, issue, or topic in a deliberate and effective way.”

In an FMEA, each of the high-risk failure modes must be addressed by effective actions that reduce risk to an acceptable level. [Read more…]

by Ray Harkins Leave a Comment

Risk Management Models

Turning Uncertainty into Informed Action

Co-authored by Mike Vella

At its core, risk management exists to protect us. It aims to reduce both the likelihood and the consequences of adverse events, whether those events affect safety, quality, cost, equipment, or project schedules.

Good risk management is not reactive. It is proactive. It assumes that future events can be influenced and, to some degree, controlled. That belief alone fundamentally changes how organizations plan, design, and operate.

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by Hemant Urdhwareshe Leave a Comment

Weibull Analysis of Right-Censored Data with a Free Software

Dear friends, we are happy to release our103rd technical video! In this video, Hemant Urdhwareshe explains and illustrates procedure to perform Weibull Analysis of right Censored data (or suspensions) using a free open-source software ‘Reliability Analytics Toolkit’. Hemant is a Fellow of ASQ and is certified by ASQ as CRE, Six Sigma Master Black Belt, CQE and CMQ/OE. This will help viewers to understand how to perform Weibull Analysis of incomplete right censored data without investing in expensive software.

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by Hemant Urdhwareshe 1 Comment

Weibull Analysis with a Free Open Source Software

Dear friends, I am releasing this 102nd video after a long gap of more than three months! I went through some critical health issues since October-2024! Now that I have recovered fairly well, I have created this interesting video. In this video, I have explained how to perform Weibull Probability Plotting and life data analysis of complete data using ‘Reliability Analytics Toolkit’.

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by Ray Harkins Leave a Comment

Cohen’s Kappa: Measuring Agreement Beyond Chance

Attribute inspection is one of the most widespread and difficult-to-control measurement methods in manufacturing. Whether inspecting machined surfaces for cosmetic defects, checking weld quality, reviewing molded parts, evaluating assembly completeness, or using go/no-go gauges, many operations depend on human inspectors to make subjective judgments. [Read more…]

by Larry George Leave a Comment

Why Weibull?

What if you don’t have lifetime data??

I searched the Internet for “Why Use Weibull Reliability?” and got 196 hits “similar sites omitted”. Some hits looked like they were generated by Chat GPT. None showed data. None told how to test or use Weibull reliability estimates. Many sell Weibull software. All require lifetime data.

Assuming a continuous, parametric distribution such as Weibull conveniently extrapolates limited, censored lifetimes to estimate MTBF, even though MTBF may be far in the future. Https://en.wikipedia.org/wiki/Weibull_distribution lists many uses for Weibull distributions. A client had me use Weibull to model durations of covered calls!

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by Hemant Urdhwareshe Leave a Comment

System Reliability Quiz and Durability Case Study

Dear friends, we are happy to release this 101th technical video on system durability estimation! The first part of the video describes the quiz. Viewers are expected to try to solve it on their own before watching the second part of the video where we have illustrated the solution using Excel.

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by Hemant Urdhwareshe Leave a Comment