Category Archives: Engineering

Consider the Decision Making First

Consider the Decision Making First

Reliability activities serve one purpose, to support better decision making.

That is all it does. Reliability work may reveal design weaknesses, which we can decide to address. Reliability work may estimate the longevity of a device, allowing decisions when compared to objectives for reliability.

Creating a report that no one reads is not the purpose of reliability. Running a test or analysis to simply ‘do reliability’ is not helpful to anyone. Anything with MTBF involved … well, you know how I feel about that. Continue reading Consider the Decision Making First

Defining a Product Life Time

An Elusive Product Life Time Definition

The following note and question appear in my email the other day. I had given the definition of reliability quite a bit of thought, yet have not really thought too much about a definition of ‘product life time’.

So after answering Najib’s question I thought it may make a good conversation starter here. Give it a quite read, and add how you would answer the questions Najib poses. Continue reading Defining a Product Life Time

The Fear of Reliability

The Fear of Reliability

MTBF is a symptom of a bigger problem. It is possibly a lack of interest in reliability. Which I doubt is the case. Or it is a bit of fear of reliability.

Many shy away from the statistics involved. Some simply do not want to know the currently unknown. It could be the fear of potential bad news that the design isn’t reliable enough. Some do not care to know about problems that will requiring solving.

What ever the source of the uneasiness, you may know one or more coworkers that would rather not deal with reliability in any direct manner. Continue reading The Fear of Reliability

Why do we use Weibull++ over JMP?

Why do we use ReliaSoft instead of JMP to Identify the Time to Failure?

This is a question someone posted to Quora and the system prompted me to answer it, which I did.

This question is part of the general question around which software tools do you use for specific situations. First, my response to the question. Continue reading Why do we use Weibull++ over JMP?

Two Ways to Think and Talk about Reliability

Two Ways to Think and Talk about Reliability

Neither includes using MTBF, btw.

And, I’m not thinking about the common language definition either.

Plus, I may have this all wrong. Here is the way I think about the reliability of something. More than ‘it should just work’ and different than ‘one can count on it to start’. When I ask someone how reliable a product is, this is what I mean.

By explaining my basic understanding we can compare notes. It is possible, quite possible, that I will learn something. As you may as well. Let’s see. Continue reading Two Ways to Think and Talk about Reliability

5 Reasons Rate of Change is Important

5 Reasons Rate of Change is Important

A simplifying assumption associated with using MTTF or MTBF implies a constant hazard rate. Some assume we’re in the useful life section of the bathtub curve. Others do not understand what assumptions they are making.

Using MTTF or MTBF has many problems and as regular reader here know, we should avoid using these metrics.

By using MTTF or MTBF we also lose information. We are unable to measure or track the rate of change of our equipment or system’s failure rates (hazard rate). The simple average is just an average and does not contain the essential information we need to make decisions.

Let’s explore five different reasons the rate of change of a failure rate is important to measure and track. Continue reading 5 Reasons Rate of Change is Important

How About Weibull Instead of MTBF?

What About Weibull, Can I Use it Instead of MTBF?

This was a follow up question in a recent discussion with Alaa concerning using a metric other than MTBF.

The term ‘Weibull’ in some ways has become a synonym for reliability. Weibull analysis = life data (or reliability) analysis. The Weibull distribution has the capability to describe a changing failure rate, which is lacking when using just MTBF. Yet, it is suitable to use ‘Weibull’ as a metric? Continue reading How About Weibull Instead of MTBF?

Life Data Analysis with only 2 Failures

Life Data Analysis with only 2 Failures

Here’s a common problem. You have been tasked to peer into the future to predict when the next failure will occur.

Predictions are tough.

One way to approach this problem is to do a little analysis of the history of failures of the commonest or system. The problem looms larger when you have only two observed failures from the population of systems in questions.

While you can fit a straight line to two failures and account for all the systems that operated without failure, it is not very satisfactory. It is at best a crude estimate.

Let’s not consider calculating MTBF. That would not provide useful information as regular reader already know. So what can you do given just two failures to create a meaningful estimate of future failures? Let’s explore a couple of options. Continue reading Life Data Analysis with only 2 Failures

Exposing a Reliability Conflict of Interest

Is Your Organization Compromising Reliability Performance Due to a Reliability Conflict of Interest?

Kirk Gray wrote the article titled Exposing a Reliability Conflict of Interest on Accendo Reliability. He talked about a recent article discussion the maintenance costs for the F-35 fighter jet program and how the companies designing the system make a significant profit selling spare parts or maintenance services.

If you count on the profit from the system you design failing, you have an inherent conflict of interest concerning creating a reliable system.  If you create a reliable product you lose money. Continue reading Exposing a Reliability Conflict of Interest

Should One Profit From Failures?

Should One Profit From Failures?

“Do not improve reliability as it cuts into our repair activity profits.” Is this a way to run a reliability program?

I’ve seen this in action and that company is no longer in business. In another situation the field service department withheld vital information to improve products lest his department (and self-importance) dwindle.

Is this a bad business model, or is it just my thinking it not so smart? Continue reading Should One Profit From Failures?

A Life Data Analysis Challenge

old machinery couplingHere is a Challenge: Life Data Analysis

Some years ago a few colleagues compared notes on results of a Weibull analysis. Interesting we all started with the same data and got different results.

After a recent article on the many ways to accomplish data analysis, Larry mentioned that all one needs is shipments and returns to perform field data analysis.

This got me thinking: What are our common methods and sets of results when we perform life data analysis? Continue reading A Life Data Analysis Challenge

The Many Ways of Data Analysis

Given Some Data, Do Data Analysis

Let’s say we have a set of numbers, {2.3, 4.2, 7.1, 7.6, 8.2, 8.4, 8.7, 8.9, 9.0, 9.1} and that is all we have at the moment.

How many ways could you analyze this set of numbers? We could plot it a few different ways, from a dot plot, stem-and-leaf plot, histogram, probability density plot, and probably a few other ways as well. We could calculate a few statistics about the dataset, such as mean, median, standard deviation, skewness, kurtosis, and so on. Continue reading The Many Ways of Data Analysis

The Challenges in Reliability Engineering

What are the Other Challenges in Reliability

Creating a product or system that lasts as long as expected, or longer, is a challenge.

It’s a common challenge that reliability engineering and entire engineering team face on a regular basis. It’s also not our only challenge.

We face and solve a myriad of technical, political, and engineering challenges. Some of our challenges are born and carried forward by our own industry. We have tools suitable for a given purpose altered to ‘fit’ another situation (inappropriately and creating misleading results). We have terms that we, and our peers, struggle to understand.

Sometimes, we, as reliability engineers have set up challenges that thwart our best efforts to make progress.

Let’s examine a few of the self made challenges and discuss ways to overcome these obstacles permitting us to tackle the real hurdles in our path. Continue reading The Challenges in Reliability Engineering

Enabling Great Reliability Decisions

Reliability is about making the right decision, each time.

Answering Questions

A common role during a first assignment as a reliability engineering is to answer a question or accomplish a task. It may help someone to make reliability decisions.

We may be asked, as I was, how long will this new product function during use? The director of engineering wanted to know if the new design was reliable enough to meet the customer’s requirements concerning reliability. He didn’t ask it that way, yet he did have a question that needed answering.

Sometimes we run a batch of tests, conduct failure analysis on field returns, or compare the durability to two vendor subsystems. In each case, there is a question to be answered.

A decision to be made by someone else. Continue reading Enabling Great Reliability Decisions

Field Failure: A Quality or Reliability Problem

Field Failure: A Quality or Reliability Problem

When my car fails to start, as a customer I only know that my car didn’t start.

When my phone fails to turn on, or the dishwasher leaks, or the printer jams, I only know I’ve experienced an unwanted outcome.

I really do not care, at the moment, why the coffee maker is not producing my morning cup of coffee. My first thought is ‘now where do I find a cup of coffee?’ As a reliability engineer I’m naturally curious about what caused the failure and can I fix it immediately to get the morning cup brewing.

My thinking does not classify the failure or the source of the failure as a quality or reliability problem. Then why is it that some organizations split reported field failures thus? Continue reading Field Failure: A Quality or Reliability Problem