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Home » Articles » on Product Reliability » Page 7

on Product Reliability

A listing in reverse chronological order of articles by:



  • Kirk Grey — Accelerated Reliability series

  • Les Warrington — Achieving the Benefits of Reliability series

  • Adam Bahret — Apex Ridge series

  • Michael Pfeifer — Metals Engineering and Product Reliability series

  • Fred Schenkelberg — Musings on Reliability and Maintenance series

  • Arthur Hart — Reliability Engineering Insights series

  • Chris Jackson — Reliability in Emerging Technology series

by Christopher Jackson Leave a Comment

Benchmarking (by definition) Makes you Average. At Best.

Benchmarking (by definition) Makes you Average. At Best.

How heavy should you be? Perhaps this is a sensitive question. The average weight of a human is about 65.2 kg or 143.7 lbs. So if your weight is above this figure, are you ‘too heavy’? Conversely, if you are below this figure, are you ‘too light’? Being over and underweight can bring a whole raft of health consequences. 

Hopefully you would agree with me in saying that the ‘average’ human weight is not a good benchmark to use if you want to get healthier. Or at least it is not the only benchmark you should think about.

But unfortunately … many manufacturers use approaches that are embarrassingly close to this ridiculous approach to continual improvement. 

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability in Emerging Technology Tagged With: Benchmarking

by Semion Gengrinovich Leave a Comment

8D in RCA

8D in RCA

The 8D (Eight Disciplines) method is a problem-solving methodology designed to find the root cause of a problem, devise a short-term fix, and implement a long-term solution to prevent recurring problems. It was first introduced in Ford’s 1987 Team-Oriented Problem Solving manual and has since become a widely used problem-solving method, also known as Global 8D. The 8D process consists of eight disciplines, each focusing on specific aspects of problem-solving

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability Knowledge Tagged With: Root Cause Analysis (RCA)

by Christopher Jackson 4 Comments

No … 89 percent of Failures are NOT Random

No … 89 percent of Failures are NOT Random

I am constantly confronted by students, reliability engineers and other people banging fists on tables and saying …

… 89 percent of failures are random …

Firstly, 100 percent of failures are random. It’s just that there are lots of textbooks and experts telling us that a ‘random’ failure is one that happens irrespective of age. That is, a failure with a constant ‘failure rate’ where the item in question doesn’t appear to age or wear out.

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability in Emerging Technology Tagged With: Failure data

by Semion Gengrinovich Leave a Comment

Statistical Distribution – is this really important?

Statistical Distribution – is this really important?

Statistical distribution – it has important role in general life and of course in engineering specifically. So, what is all about? 

During morning commute either by bus or vehicle, you take some budget of time. From your daily routine experience, you with very high probability, can predict arrival time. You also know how much time it will take, in less ordinary cases, like slippery roads, or cars accident along you route. 

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability Knowledge Tagged With: Statistics distributions and functions

by Semion Gengrinovich Leave a Comment

What is ALT?

What is ALT?

A short introduction to accelerated life testing or ALT. It is a method used to enhance product reliability by subjecting prototypes to stress levels significantly higher than those encountered in actual use. The idea is to rapidly induce failures which is equivalent to speeding up time.

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability Knowledge Tagged With: Life testing and accelerated life testing (ALT)

by Semion Gengrinovich 2 Comments

How Many Samples I need Run for this Test?

How Many Samples I need Run for this Test?

Anybody who did some hardware test in they life, eventually will face the question of sample size. 

Probably it will be a tradeoff between the test duration and amount of samples to test.

So how much is enough? One, three, ten?

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability Knowledge Tagged With: Sample size

by Enrico Belmonte 4 Comments

Why Various Distributions Are Appropriate

Why Various Distributions Are Appropriate

Why are Weibull, lognormal, and exponential distributions more appropriate than others for modeling failure distributions?

In this article, I want to show you why Weibull, lognormal, and exponential distributions are more appropriate than others for modeling failure distributions. Instead of starting from the explanation of the most used fitting distributions in reliability engineering, I will begin with the analysis of artificial datasets created assuming specific failure behaviors. In other words, I will start from the data and not from the statistical distributions. I think that this approach can help those who deal with this topic for the first time.

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability Competence Tagged With: Statistics distributions and functions

by Christopher Jackson Leave a Comment

Only People who are Biased Think they are Not Biased

Only People who are Biased Think they are Not Biased

Many of us like to think that we can, at least sometimes, be objective. Which is the opposite of being subjective.

What does this mean? Something is ‘objective’ if it only depends on the world around it, and nothing else. Like the ‘perfect juror’ who is only swayed by facts and evidence when determining if he or she thinks someone is guilty of murder. Something is ‘subjective’ if it can be influenced … by itself. Like the ‘imperfect juror’ who decides to acquit a murder suspect regardless of the evidence … because the suspect is his or her brother. This is called bias.

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability in Emerging Technology

by Christopher Jackson Leave a Comment

Boeing is Steering Harder into its Spiral of Death

Boeing is Steering Harder into its Spiral of Death

Boeing has somehow managed to make the bad public relations created by those pesky onboard batteries catching fire in 2013 practically disappear. Not through good management. But through a never-ending series of disasters and catastrophes that shows no sign of letting up which is dominating Boeing’s news cycle that there is no remaining airtime for missteps like those battery fires.

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability in Emerging Technology

by Christopher Jackson Leave a Comment

Leadership and the Failure of the Apple Car

Leadership and the Failure of the Apple Car

Apple recently did something that it isn’t in the habit of doing. And that is – admitting failure. After spending $ 10 billion on ‘Project Titan’ whose aim was to produce a ‘really cool car,’ Apple decided to pull the pin and cancel it.

Simplifying Apple’s Project Titan ambitions to something as pithy as creating a ‘really cool car’ might seem a little condescending. The problem for Apple was that unfortunately, this was the practical truth. And that is why it failed.

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability in Emerging Technology

by John Kreucher 3 Comments

Warranty – The Bad Old Days and What Came After

Warranty – The Bad Old Days and What Came After

If I must date myself, I cut my teeth as a product development engineer in the automotive industry in the bad old days when warranty terms were shockingly poor.  Let’s examine this through the lens of my first new car which I purchased in 1984.  Why was my warranty coverage so bad, what drove the significant improvements seen in the industry since that time, and how do we now validate our products to keep it that way?

[Read more…]

Filed Under: Articles, on Product Reliability, Product Validation

by Christopher Jackson Leave a Comment

Confidence is a Measure of You, Not Your Product

Confidence is a Measure of You, Not Your Product

We like to think we make decisions based on information. We don’t. We make decisions based on emotions. And the most important emotion we rely upon for decision-making is confidence. We can be provided all the information in the world, but if we can’t understand it, trust it or believe it, we look for confidence in other ways. Often to disastrous outcomes. 

The number of ‘well-funded’ production efforts full of ‘very smart people’ that routinely generate expensive but unreliable products is sadly, very high. And it all comes down to the wrong types of confidence that well-paid decision-makers chase. 

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability in Emerging Technology

by Debasmita Mukherjee Leave a Comment

Data Storytelling Using Histogram

Data Storytelling Using Histogram

In the current century, data is ubiquitous but how to make use of it to drive product decisions can take time and effort. Data visualization is a useful technique to identify patterns in a dataset and derive exploratory statistics to analyze trends.

[Read more…]

Filed Under: Articles, Field Reliability Data Analysis, on Product Reliability

by Fred Schenkelberg 3 Comments

When Past Reliability is Good

When Past Reliability is Good

Let’s say that you and your team have done well. Your products or systems are reliable. They work, customers are happy, and the cost of unreliability is low. That’s the goal, right? Congratulations are in order.

However, enjoying great reliability performance was the goal. It is what we expected. It’s what we worked to achieve. Now what?

[Read more…]

Filed Under: Articles, Musings on Reliability and Maintenance Topics, on Product Reliability

by Enrico Belmonte Leave a Comment

Stochastic Nature of Stress and Strength

Stochastic Nature of Stress and Strength

Since I published my first contribution about reliability, I’ve received a number of emails asking where the stress and strength distributions come from (Figure 1).

[Read more…]

Filed Under: Articles, on Product Reliability, Reliability Competence

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