# What is Reliability?

### Guest Post by Martin Shaw

In today’s complex product environment becoming more and more electronic, do the designers and manufacturers really understand what IS Reliability ??

It is NOT simply following standards to test in RD to focus only on Design Robustness as there is too much risk in prediction confidence, it only deals with the ‘intrinsic’ failure period and rarely has sufficient Test Strength to stimulate failures. Continue reading What is Reliability?

# Failure Happens – It Is What Happens Next That Matters

One of the benefits of reliability engineering is failure happens.

Nothing made, manufactured, or assembled will not fail at some point. It is our desire to have items last long enough that keeps us working. Since failures happen, our work includes dealing with the failure.

## Not My Fault

Years ago while preparing samples for life testing at my bench, I heard an ‘eep’ or a startled sound from a fellow engineer. It was quickly followed by an electrical pop noise and a plum of smoke.

Something on the circuit board she was exploring had failed. With a pop and smoke. She didn’t move.

At this point, my initial amused response turned to concern for her safety. She was fine, just startled as the failure was unexpected. She quickly claimed it wasn’t her fault.

It was her design, she selected and assembled the parts, and she was testing the circuit. Yet, it wasn’t her fault. She did not expect a failure to occur (a blown capacitor – which we later discovered was exposed to far too much voltage), thus it was not her fault.

We hear similar responses from suppliers of components. It must have been something in your design or environment that caused the failure, as the failure described shouldn’t happen. It’s not expected.

Well, guess what, it did happen. Now let’s sort out what happened and not immediate assign blame for who’s fault it is.

The ‘not my fault’ response so a failure is not helpful. Failures are sometimes the result of a simple error and quickly remedied. Other are complex and difficult to unravel. The quicker we focus on solving the mystery of the cause of the failure, the quicker we can move on to making improvements.

## Warranty

With possibly too many ‘not my fault’ responses, laws now enjoin the manufacture of products to stand behind their product. If a failure occurs, sometimes within specific conditions, the customer may ask for a remedy from the supplier.

If failures did not happen there would be no such thing as a warranty.

A warranty is actually a legal obligation, yet has turned into a marketing tool. A long warranty implies the product is reliable and by offering a long warranty the manufacturer is stating they are shifting the risk of failure to themselves.

A repair or replacement is generally not adequate recompense for a failure, yet it provides some restitution. In most cases, it only provides peace of mind, if the item doesn’t fail.

The warranty business has become an industry in of itself. Selling, servicing, and honoring warranties is something that others can deal with outside your organization. The downside is the lack of feedback about failure details so you can affect improvements. A manufacturer shouldn’t hide behind their warranty policy, nor ignore the warranty claim details. It is one-way a customer can voice their expectations concerning product reliability. You should listen.

## Repair services

My favorite outsourced repair service story involved a misguided payment structure.

If you pay a repairman based on the value of the components replaced, they will likely always replace the most expensive components. If the repair is accomplished by resetting a loose connector, nothing is replaced, and the repairman is not compensated for the diagnostic work and effective repair. If he instead immediately replaced the main circuit board, and in the process reseating most of the connectors, the repair is fast, effective, and he is handsomely rewarded.

See the problem?

When a failure occurs, it may be natural to offer a repair service as the remedy. It should be quick (not a two-week wait as with my local cable company to restoring a fallen line), and efficient for all parties involved. For the owner of the equipment, we want the functionality restored as quickly as possible and cost effectively as possible. For the manufacture of the equipment, we want cost effectiveness, plus the knowledge concerning the failure.

Does your repair service provide for the needs of both parties as well as the repair technician?

## Fail safe

Sometimes when a failure occurs nothing happens. We might not even notice the failure occurs. Other times the product simply goes ‘cold’ or a function is lost. Nothing adverse, no pop or smoke, occurs.

We call this failing safe. It’s more complicated than my simple explanation, yet it is the desired repose to a failure. The product itself should not create more damage, cause harm, place someone in peril. It should fail safely and preferably quietly.

If the ignition falls from the ignition switch, which may be considered a failure to retain the key within the switch, the driver should not lose control of the vehicle. This is in part a safety feature, yet is also a common expectation that the failure of a system should not create other problems.

Failure containment is related.

How does your product fail? Safely?

## Maintenance

For some failures, such as the degradation of lubricants, we perform maintenance. When the brake pads or tire tread wears to marginally safe level we replace the brake pad or tire. If we can anticipate the failure pattern we perform preventive maintenance.

Creating a maintainable piece of equipment is one response to failures. It allows creating complex equipment with failure prone elements. Through maintenance, we are able to restore the system to operation or avoid unexpected downtime. If failures didn’t occur, we wouldn’t need maintenance.

We have some control over the nature of the maintenance activities. For some types of failures, we can only execute corrective maintenance. For others, we can use preventative methods. The idea is to anticipate and avoid the widest range of failures through effective maintenance practices, that remains cost effective.

Adding maintenance practices in response to system failures is not the duty of the owner of the equipment. It is a design function to anticipate the system failures that may occur and devise the appropriate maintenance plan to thwart unwanted failures from occurring. The two parties actually have to work together to make this work well.

## Expectations

When I buy a product, I know that some proportion of products like the one I just purchased will failure prematurely. I just do not want or desire mine to fail. My expectation is the one I select at the store is a good one. It won’t let me down, stranded, or injured. That is my expectation.

When a failure does occur and I value the functionality the product provides I will want to restore the unit via repair or replacement, sometimes via a service contract or warranty or repair center. To a large degree, my expectation is after a failure all will go well.

As the manufacture of products, when a failure occurs, your expectations may include learning from the failure to make improvements. Or it should.

We know we cannot anticipant nor avoid every failure that may occur. The expectation on both sides is to make robust and dependable products that provide value for all involved. When that approach fails, we fail.

## Failure Happens

In response to a failure, it’s how the product, customer, and manufacture responds that matters. A simple failure can turn into a disaster for all involved. Or the failure can provide insights leading to breakthrough innovations and new opportunities.

It’s how we respond that matters.

How do you respond to failures?

# Are the Measures Failure Rate and Probability of Failure Different?

Failure rate and probability are similar. They are slightly different, too.

One of the problems with reliability engineering is so many terms and concepts are not commonly understood.

Reliability, for example, is commonly defined as dependable, trustworthy, as in you can count on him to bring the bagels. Whereas, reliability engineers define reliability as the probability of successful operation/function within in a specific environment over a defined duration.

The same for failure rate and probability of failure. We often have specific data-driven or business-related goals behind the terms. Others do not.
If we do not state over which time period either term applies, that is left to the imagination of the listener. Which is rarely good.

## Failure Rate Definition

There at least two failure rates that we may encounter: the instantaneous failure rate and the average failure rate. The trouble starts when you ask for and are asked about an item’s failure rate. Which failure rate are you both talking about?

The instantaneous failure rate is also known as the hazard rate h(t)

￼￼￼￼$\displaystyle h\left( t \right)=\frac{f\left( t \right)}{R\left( t \right)}$

Where f(t) is the probability density function and R(t) is the relaibilit function with is one minus the cumulative distribution function. The hazard rate, failure rate, or instantaneous failure rate is the failures per unit time when the time interval is very small at some point in time, t. Thus, if a unit is operating for a year, this calculation would provide the chance of failure in the next instant of time.

This is not useful for the calculation of the number of failures over that year, only the chance of a failure in the next moment.

The probability density function provides the fraction failure over an interval of time. As with a count of failures per month, a histogram of the count of failure per month would roughly describe a PDF, or f(t). The curve described for each point in time traces the value of the individual points in time instantaneous failure rate.

Sometimes, we are interested in the average failure rate, AFR. Where the AFR over a time interval, t1 to t2, is found by integrating the instantaneous failure rate over the interval and divide by t2 – t1. When we set t1 to 0, we have

$\displaystyle AFR\left( T \right)=\frac{H\left( T \right)}{T}=\frac{-\ln R\left( T \right)}{T}$

Where H(T) is the integral of the hazard rate, h(t) from time zero to time T,
T is the time of interest which define a time period from zero to T,
And, R(T) is the reliability function or probability of successful operation from time zero to T.

A very common understanding of the rate of failure is the calculation of the count of failures over some time period divided by the number of hours of operation. This results in the fraction expected to fail on average per hour. I’m not sure which definition of failure rate above this fits, and yet find this is how most think of failure rate.

If we have 1,000 resistors that each operate for 1,000 hours, and then a failure occurs, we have 1 / (1,000 x 1,000 ) = 0.000001 failures per hour.

Let’s save the discussion about the many ways to report failure rates, AFR (two methods, at least), FIT, PPM/K, etc.

## Probability of Failure Definition

I thought the definition of failure rate would be straightforward until I went looking for a definition. It is with trepidation that I start this section on the probability of failure definition.

To my surprise it is actually rather simple, the common definition both in common use and mathematically are the same. There are two equivalent ways to phrase the definition:

1. The probability or chance that a unit drawn at random from the population will fail by time t.
2. The proportion or fraction of all units in the population that fail by time t.

We can talk about individual items or all of them concerning the probability of failure. If we have a 1 in 100 chance of failure over a year, then that means we have about a 1% chance that the unit we’re using will fail before the end of the year. Or it means if we have 100 units placed into operation, we would expect one of them to fail by the end of the year.

The probability of failure for a segment of time is defined by the cumulative distribution function or CDF.

## When to Use Failure Rate or Probability of Failure

This depends on the situation. Are you talking about the chance to failure in the next instant or the chance of failing over a time interval? Use failure rate for the former, and probability of failure for the latter.

In either case, be clear with your audience which definition (and assumptions) you are using. If you know of other failure rate or probability of failure definition, or if you know of a great way to keep all these definitions clearly sorted, please leave a comment below.

# Getting Enough of the Right Professional Development

Learning the basics of reliability engineering is where we all start. Mastering the range of skills and techniques is a never ending quest.

Improving, maintaining, expanding your reliability engineering professional skills takes many forms. There are plenty of options and sources to support your education, yet are do getting enough of the right material?  Continue reading Basic Outline to Craft Your Professional Development Plan

# Are Your Reliability Engineering Technical Skills Good Enough?

How do you know? How would you know?

There is a lot to know concerning the technical aspects of reliability engineering. From calculating summary statistics to discovering the root cause of a failure, the body of knowledge you should master as a reliability personal is expansive. Continue reading Are Your Reliability Engineering Technical Skills Good Enough?

# Lifetime Evaluation vs. Measurement. Part 3.

is more powerful than being smart.

—Astro Teller

## Guest post by Oleg Ivanov

A common approach for “no failure” testing is the use of the well-known expression

$\displaystyle (1) \quad 1-CL={{R}^{n}}$

where CL is a confidence level, R is a required reliability, n is a sample size. Its parent is a Binomial distribution with zero failures. This expression is like a poor girl: Continue reading Lifetime Evaluation vs Measurement Part 3

# How to Avoid Delivering Bad Data

We gather and report loads of data nearly every day.

Is your data “good data”? Or does it fall into the “bad data” category?

Let’s define the difference between good and bad data. Good data is accurate, timely, and useful. Bad data is not. It may be time to look at each set of data you are collecting or reviewing and judge if it’s good or not. Then set plans in motion to minimize the presence of bad data in your organization.

## Good data is accurate

By this I mean it truly reprints the items or process being measured.

If the mass is 2.3 kilograms, then the measurement should be pretty close to 2.3 kg. This is a basic assumption we make when reviewing measurements, yet when was the last time you checked? Use a different measurement method, possible a known accurate method to check.

Measurement system analysis includes a few steps to determine if the gage making a measurement is true or not. Calibration may come to mind, as it is a step to verify the gage readings are reflecting standard measures. A meter is a meter is a meter across the many ways we can measure distance.

It also includes checking the common sources of measurement error:

• Repeatability
• Reproducibility
• Bias
• Linearity
• Stability

You may also want to understand the resolution or discrimination of the measurement process.

If these terms and how one goes about checking for accuracy, it may be time to learn a little about MSA.

## Good data is timely

If the experiment results are available a week after the decision to launch the product, it will not be considered in the decision. It is not useful for the decision concerning product launch. If the data was available it may alter the decision. Late, we will not know.

Timely means it is in time for someone or some team to make a decision. Ideally, the data is available immediately. When a product fails in the field, we would like to know right away, not two or three month later. If a production line becomes unstable, knowing before another unit of scrap is produced would be timely.

Not all data gathering and reporting is immediate. Some data takes months or an entire year to gather. There are physical constraints in some situation that day the gathering of data. For example is takes on average 13 minutes, 48 seconds, for radio signals to travel from a space probe orbiting Mars to reach Earth [1]. If you are making important measurements on Earth it should be a shorter delay.

The key point here, is the data should be available when it is needed to make decisions.

## Good data is useful

Even if the data is accurate and timely is may not be useful. The data could be from a perfect measurement process, yet is measuring something we do not need to know or consider. The data gathered does not help inform us concerning the decision at hand.

For example, if I’m perfectly measuring production throughput, it does not help me understand the causes of the product line downtime. While related to some degrees, instead of the tally of units produced per hour, what we really would find useful is data concerning the number of interruptions to production, plus details on the root cause of each.

Setting up and maintaining the important measurements is difficult as we often shift focus based on the current data. We spot a trend and want to learn more than the current data can provide. The idea is we should not setup and only use a fixed set of data collection processes. Ideally your work to gather data is driven by the need to answer questions.

• Is the maintenance process improving the equipment operation?
• Is our manufacturing process stable and capable of creating our product?
• Will the current product design meet life expectations/requirements?
• Have we confirmed the new design ‘fixed’ the faults seen in the last prototype?

We have questions and we gather data to allow us to answer questions.

How would you describe the data you will look at today? Good or Bad? And more importantly, do you know if your data is good or bad?

Time delay between Mars and Earth, Thomas Ormhston, posted 5/8/2012,  European Space Agency, Mars Express Blog, http://blogs.esa.int/mex/2012/08/05/time-delay-between-mars-and-earth/ accessed 4/29/2016

# Lifetime Evaluation vs. Measurement. Part 2.

## Guest post by Oleg Ivanov

A result of life testing can be measurement or evaluation of the lifetime.

Measurement of the lifetime requires a lot of testing to failure. The results provide us with the life (time-to-failure) distribution of the product itself. It is long and expensive.

Evaluation of the lifetime does not require as many test samples and these tests can be without failures. It is faster and cheaper [1]. A drawback of the evaluation is that it does not give us the lifetime distribution. The evaluation checks the lower bound of reliability only, and interpretation of the results depends on the method of evaluation (the number of samples, test conditions, and the test time). Continue reading Lifetime Evaluation vs. Measurement. Part 2.

# Extend Your FMEA Process with Mechanisms

One of the issues I’ve had with failure modes and effects analysis is the focus on failure modes.

The symptoms that the customer or end user will experience are important. If a customer detects that product has failed, that is a failure. The FMEA process does help us to identify and focus on the important elements of a design that improve the product reliability. That is all good.

The issue is the FMEA process doesn’t go far enough to really aide the team focus on what action to take when addressing a failure mode. The process does include the discussion of causes of the failure mode. The causes are often the team members educated opinions on what is likely to cause the failure mode. Often the description of the a cause is a failed part, faulty code, or faulty assembly.

Generally the discussion of causes is vague.

## Failure Mechanisms versus Failure Modes

Failures modes are best described as what the customer experiences (no power, loss of function, etc.). Failure mechanisms are the root physical or chemical anomaly that leads to the existence of the failure mode. While we want to remove failure modes, we have to solve, remove, or mitigate failure mechanisms along the way.

The traditional FMEA process in my experience often provides vague classes of causes, hints at potential failure mechanisms, or avoids specifying mechanisms entirely. The actions items from the FMEA study then include investigations to find and understand the actual failure mechanisms (at best) or attempt to address vague classes of mechanisms with broad sweeps of monitoring, testing, or design changes.

Instead focusing the discussion on causes of failures at the level of failure mechanisms, enhances the discussion. Instead of talking about the causes as a component failure, it changes to what happens such that the component fails. Instead a vague average failure rate, it becomes a discussion about design or process errors or variation that leads to the components demise.

The hard part of this approach is the sheer number of ways (root causes) that an item may fail. Consider a simple component solder joint. The potential root causes includes:

• Contamination
• Corrosion
• Dendrite growth
• Cracking
• Shear fracture
• Flex cracking
• Gold embrittlement

And many others potential issues. Even these brief descriptions may have underlying causes which are the elements requiring attention in order to solve.

## Fault Tree Analysis (FTA) and FMEA

Detailing all possible root causes of each failure mode would be tedious and I would suggest unnecessary. One approach I’ve seen is the common approach to FMEA, where we explore the class or basic expected types of root causes that lead to the listed failure mode. Then for the lines in the FMEA study that percolate to the items requiring attention, we then conduct a detailed FTA that flushes out the range and relative frequency of occurrence of the many different underlying failure mechanisms that lead to a specific failure mode.

If the primary cause of a failure mode is a faulty component, then what are the specific mechanisms that lead to a component being faulty. FTA is the right tool here. Used on conjunction with the highest risks identified in the FMEA permit the team to understand and solve or mitigate the right elements in the design or process to make a difference. Being specific with actions that make a difference is the key.

With your work to identify and resolve risks to reliability performance, how do you insure the solutions are actually solving the right problem? What works for you in your organization? How do you extend your FMEA work into effective action?

# Do You Have Enough Data?

To make informed decisions you need information.

To form conclusions you need evidence and a touch of logic.

To discover patterns you need data.

In each case, and others, we often start with data. The data we have on hand, or can quickly gather.

We organize data into tables, summaries into reports, display in dashboards, and analyze the results to form decisions. Continue reading Do You Have Enough Data?

# The People Skills of a Good Reliability Engineer

Having the technical and business skills is not sufficient to be a good reliability engineer.

You must also work with other people. With your peers, across the management team, with suppliers, contractors, and customers.

The ability to work well with others is often complex and situational. Being aware of a few basic skills will allow you learn and improve. Prette and Prette define social competence as the social skills

that meet the different inter-personal demands in the workplace in order to achieve the goals, preserve the well-being of the staff and respect the rights of each other.

A. Del Prette and Z. A. P. Del Prette, Psicologia das relac ̧o ̃es interpessoais: viveˆncias para o trabalho em grupo, Vozes, Petro ́ polis, 2001.

An engineer needs an awareness of the social situation and how their behavior influences others, along with a capability to correctly understand the behavior and needs of others. The concepts discussed under emotional intelligence include:

• self-awareness
• self-regulation
• Motivation
• Empathy
• and social skills

Goleman, D., Emotional Intelligence: Why It Can Matter  More than IQ. New York: Bantam Books (1995).
Goleman, D., Working with Emotional Intelligence.  London: Bloomsbury Publishing (1998).

The ability to influence others or to aide in understanding a technical situation relies on effective communication. Beyond presenting the facts, finding, and conclusions, your communication must also build upon the audiences’ current understanding and capability. Also, our presentation must address the needs and expectations of the audience. The audience needs are often unstated, thus the need for your ability to correctly assess the social situation.

## A Meeting Example

Let’s say two engineers join a meeting to discuss an engineering problem that requires a solution. One engineer, Juan, has social skills and the other, Tomas, does not. As the team assemblies Juan arrives a minute or two early and greets his co-workers and responds to greetings and comments pleasantly. Tomas arrives on time, does not greet anyone and focuses on his laptop catching up on a few emails messages till the meeting is called to order.

A member of the team opens with a short review of the specific technical challenge and as she started with the review of what is known to date, is interrupted by Tomas. Tomas launches into his solution for the problem and remarks that the remainder of the meeting is pointless as he already has an appropriate solution to implement. The solution is not obvious to the remainder of the group which frustrates Tomas as he repeats his assertion that he has a solution. There is social tension building which Tomas does not recognize.

Juan does sense the discontent between Tomas and the rest of the team. Juan does not fully understand the problem nor Tomas’ solution, yet injects a few questions that help guide Tomas to guide the team to better understand the problem and proposed solution. Juan facilitates a discussion between those with knowledge of the problem so the entire team fully understands the issue, plus assists Tomas restate the proposed solution again to help everyone understand the proposal.

The story of this meeting could continue, with more elements of lack of social awareness and skills and possible methods to create progress. It is situations without someone like Juan having the awareness and social adeptness to facilitate effective and socially acceptable communication, that likely end poorly.

Finding a solution is not the only goal of a problem solving meeting. It is finding a solution that the team can implement effectively. This requires the team understand both the problem and the solution. Furthermore, the one meeting is likely part of series of regular engagements for this team, thus impacts the ability of the team to work cohesively going forward.

When social behavior elements such as discussions, questions, and proposals, for example, do not include consideration of the recipients situation that social friction occurs. Those around Tomas may feel belittled, devalued, excluded or ignored. Those around Juan feel heard, included, and accepted. The ability of Juan to adjust his behavior based on his awareness permits the team to hear and understand any proposal, including those from social inept people.

To make a potentially long story short, even is Tomas had the correct solution for the problem, it was Juan’s people skills that permitted the team to find and implement a solution. Juan will likely advance in his career while Tomas will not.

If you are not familiar with emotional intelligence you may want to read a few introductory articles. If you have not examined your ability communicate with individuals or groups, or you have wondered how to improve your ability to influence those around you, look for material (articles, books, seminars, courses) that provide a framework to understand how to communicate effectively.

When I first became an engineer the focus on my education and training focused on technical skills. Later I learned the importance of social skills and found that my technical prowess (little that it was) flourished as others were able to understand and accept my ideas and solutions. Plus, my contributions to meetings helped with the acceptance of other better solutions.

There are a lot of talented people all around us. Our ability to work with them enhances our ability to implement engineering solutions that meet our business and customer expectations. Plus, working well with our team make our work a bit more enjoyable.

# The Business Skills of a Good Reliability Engineer

Knowing how estimate sample size or create a Weibull plot is not enough today.

Just having technical skills, while essential, is not sufficient.

Having a master of business administration (MBA) may be helpful it is not required, yet knowing the warranty and brand cost per failure is essential.

You also need to know which analysis to conduct and how it fits into the larger program, organization, and how it impacts your customers. You need to know the business side of your work as well.

You need to understand the business connection as you create plans and finalize analysis. Each test proposed should include a business connection. Each improvement proposed has to balance with the other priorities and objectives and remain compelling.

## What is Important to Your Organization?

I don’t know as I write this what is important to your organization today. It varies, even within an organization and over time. You do need to know what is important and why to become a good reliability engineer.

It is not enough to do what someone tells you to do. At first that may get you starting yet how you connect your work to adding value become essential. Practice finding the connection with every task.

• When do you need this information?
• When will this need an initial review?
• When do you need a budget estimate?
• Who will review this report?
• Who will need this information?
• What level of reliability knowledge does the audience have?
• What level of detail is necessary?

And, so on…

The idea is to find who needs what by when and why?

This helps you plan, focus and deliver what is considered important at the moment in your organization.

## Typical Priorities

For a high volume consumer product sold during the holiday period, time to market may be the top priority. This is because a delay to shipping means the loss of sales for the year. Missing the deadline is not an option. Thus, your work as a reliability engineer has to focus on how you can minimize the risk to any delays.

Now, you know that finding a critical reliability issue late in the process may delay the program, therefore focusing on reducing the chance of a late discovery is your focus. Early testing and development work on the highest risk element may help you identify reliability risks that have a long lead time to test and evaluate.

For a industrial product with relatively low volume the time to market pressure is not as intense. In this case, the brand image may be paramount. Thus getting the initial units as reliability as customer expect becomes an overriding priority.

One of the issues with this situation is the lack of prototype systems to evaluate. You may not have the capability to test full systems in any quantity prior to to the start of production, if ever. Thus, you work to identify and characterize each potential failure mechanisms becomes critical. The ability to create a viable system model allows you to prioritize your work on improving the critical few elements that will impact system reliability performance.

Other priorities may focus on cost reduction, cutting edge feature sets, or ease of use. Your organization likely has a clear priority. It’s then up to you to connect your work in reliability engineering to that priority.

## Now Connect Each Reliability Task to the Value it Provides

For each reliability task proposed or delivered what is the value it provides connected to the primary priority (or secondary priority) in a clear and concise way. If the task or activity doesn’t add value, why are you doing it?

In the high volume consumer product situation, reducing the risk of a shipment delay provide value. Let’s say you are proposing HALT early in the program. How would that add value? By potentially identifying design or manufacturing faults if discovered late in the program would delay the project, then you arguably reduce the risk of delays by some amount.

For the low volume complex equipment situation, a HALT would improve the ability of the team to find and solve complex issues that may otherwise go undetected. Again, HALT would add value. In each case there is not a hard and fast formula yet there is a clear step by step connection between the task and the value to the organization.

## Summary

There are two steps here. One understand the business and customers to the extent that you clearly understand what is important. Second, articulate the value related to the business priorities for each reliability task or activity.

To see more examples and ways to show value, see the book Finding Value: How to Determine the Value of Reliability Engineering Activities.

Your skill at connecting your work to value enhances your ability to focus on what is important and necessary. Thus it helps your customers, organization and your career.

## Guest Post by Oleg Ivanov

How can we tell whether an iron is hot enough? The answer is obvious: We can measure temperature by using a thermocouple and a meter. But, in practice, we lick our finger and touch the iron. Sizzle…. Yes, it’s hot!

We know a priori the boiling temperature of water and we can evaluate the temperature of the iron. This method has a lower cost. Continue reading Lifetime Evaluation v Measurement

# The Technical Skills of a Good Reliability Engineer

The fundamental technical skills, as I see it, have to include statistics and root cause analysis skills. This skill set is one of three broad areas introduced in the article, What Makes the Best Reliability Engineer?

I would say these are the minimum technical skills for a good reliability engineer. Able to calculate sample size requirements, understand a dataset, and correctly determine the root causes of a failure.

There are others skills that would be great to include, such as electrical, mechanical and software engineering, plus materials science, physics, and chemistry. Yet, what separates a good reliability engineer from other types of engineering is our ability to plan and analyze life tests and to truly understand how and why failures occur.

## Statistics

This is often considered the same as leaping tall buildings with a single bound with respect to skill level.

Few enjoyed their undergraduate statistics class and recently fewer campuses require a stats course. Statistics is the language of variation and is essential for our understanding of the world our products experience.

If every product met the exact specifications of the design and only operated in one set of environmental and use conditions, we would have fewer field failures. If every failure mechanism led to failure exactly the same way within each and every product, we would have far fewer field failures.

Variability may lead to elements of a product being out of spec, or drifting/wearing to an out of spec conditions, thus failing. Variability may also lead to changes in the stress/strength relationships, again increasing the number of failures over time.

The ability of a good reliability engineer to use available data and statistical techniques to:

• Estimate sample size requirements for environmental testing
• Analyze vendor life testing results
• Summarize field failure and warranty datasets

Is just the start of our expected statistical prowess. We also need statistical skills to:

• Monitor and control processes
• Design and analyze screening and optimization design of experiments
• Review and identify field failure trends and unique failure mechanisms

Your ability to use the right tool to quickly solve a problem may span statistical process control, hypothesis testing, regression analysis, and life data analysis all before noon. That may well be like stopping a speeding bullet level of skill.

You may need to master all these elements of statistics if you’re working as a lone reliability engineer, or rely on a trusted colleague is so fortunate. Either way you need to understand enough statistics to know when and how to apply this set of technical skills.

## Root Cause Analysis

Failure mechanisms are hard science – even the human factors related failures. Failures occur because something occurs at an atomic, molecular, code or interaction level that precipitate an error or fault to manifest.

Your technical skill includes understanding the range of possible errors and faults that may occur with your product and how to avoid, minimize or mirage each one. It may not be possible to anticipate and fully understand every possible failure mechanisms, thus we focus on the most likely and common, plus continue to learn about those new (or interesting) failure mechanisms that appear.

A second element to this set of skills is the ability to deduce the root cause of a failure. Given a failure, you should be able to conduct the root causes analysis to determine the underlying failure mechanism and initiating circumstance. This permits the team to take corrective action that actually works.

The skill set includes

• Gathering evidence and understanding the relationships and contributing factors
• Delving into the unseen elements (microscopes, cross sections, chemical analysis, etc.)
• Replicating the failure at will

The root cause analysis skill may rely on tools like x-rays and thermal imaging tools, some operated by specialists, yet you need to know which tools to employ and how to interpret their results. It may be fun to explore failures in a well furnished failure analysis lab, yet you need to focus on solving the mystery of what caused the failure.

You also need to be well versed in how to proceed from the “crime scene” (or instance of failure location), through symptoms, to non-destructive and destructive testing. You need to build your “case” based on evidence and logic, plus a healthy dose of engineering knowledge of the fundamental elements involved.

If working as the lone reliability engineer, you certainly need to establish an ongoing relationship with a failure analysis lab. In other words, do not rely on your vendors, do the failure analysis work under your organizations control with your own lab or contracted facility.

Get the information your team needs to solve problems or to avoid future problems by exercising your technical root causes analysis skills.

## Good Reliability Work

To be good, I’m suggesting you have to have robust skills in statistics and root cause analysis. Do you agree? What else would you argue is essential to be a good reliability engineer?

# WIIFT and Reliability Measures

WIIFT is “what’s in it for them”. Similar to what’s in it for me, yet the focus is your consideration of what value are you providing your audience.

As a reliability engineer you collection, analyze and report reliability measures. You report reliability estimates or results. Do you know how your audience is going to use this information?

Consider WIIFT when reporting reliability. Continue reading Considering WIIFT When Reporting Reliability