Choosing a product or a service to buy is a complex process. Your own tastes play an important role, of course, but very often product reliability is what impacts your decision most of all. It is especially important when you are looking at something that can potentially serve you for many years to come. Nobody likes spending a ton of money on a device that works right now but will fail in a couple of months.
However, we can all agree that nothing lasts forever. Any product or system can fail, which is why warranties exist. But how can you make your product fail less frequently and define the best ways to cope with failures that do occur? Reliability engineering is the answer to making your product more dependable. Its methods and reliability techniques traditionally deal with manufacturing processes but can be successfully applied to multiple industries, including software engineering.
So, what exactly is reliability engineering and why might it be crucial to your business? Let's find out.
What does reliability mean?
If we want to understand how reliability engineering works though, it is necessary to fully understand what reliability itself means first. This term is often mixed up with availability, durability, and even quality itself.
Quality in reliability engineering
Quality is something that might be considered a wider term, and often might be difficult to explain. One of the popular definitions of quality determines it as being capable of fulfilling the intended function and doing so well enough to satisfy the expectations of customers. One aspect that marks the difference between quality and reliability is time. When we speak of quality, we usually mean that a certain product or system meets high standards at a given moment in time. A reliable product will be able to keep meeting these standards of performance over a period of time if the conditions in which it operates remain normal.
We took a closer look at Quality Assurance and Quality Control in our previous article. Check it out to learn more about the differences between them.
Obviously, we can't predict the future and find out when exactly a certain component or system will fail. Reliability calculation always describes probability because it can't ensure 100% certainty. Any product or system’s reliability also changes over time. It reduces the longer you use the product.
Durability in reliability engineering explained
Durability might seem very similar to reliability since this concept also deals with functioning over a period of time. The main difference here is that both concepts revolve around failures but while reliability is focused on making failures fewer and less frequent, durability is all about the total time when the product can still function after it encounters failures.
In IT there is another popular term that is often confused with reliability. The availability of a system is a concept that deals with the percentage of time during which the system can perform the required tasks and remain fully operational, or available. Less system downtime means customers are happier. The maintainability of the system also plays an important role here. If scheduled maintenance processes are performed in due time, the system experiences fewer failures, which increases its availability.
All this helps us to better understand the importance of reliability. Since it is one of the dimensions of quality, if your product isn't reliable, it won't be of truly high quality. Higher reliability and maintainability directly impact the durability and availability of your system or component.
Reliability engineering objectives
By definition, reliability engineering is a subfield of systems engineering that is concerned with using engineering knowledge to make products more reliable. There are several important goals that reliability engineering can help you to achieve.
First and foremost, reliability engineers use dedicated techniques (more on that in subsequent sections) and apply engineering knowledge to decrease failure rates or make failures less probable or frequent. This goes hand in hand with failure analysis, which includes determining the root causes of failures that still happen despite preventive maintenance and developing solutions for these issues.
Another aspect that reliability engineers deal with is designing strategies that are implemented to cope with failures that eventually occur because the root issue hasn't been fixed. A reliability engineer also typically works on designs of new systems or products, trying to predict the most likely failure rate and overall reliability. However, analyzing reliability data and improving reliability should happen continuously over the course of a project, not only at the beginning, and that is why you need reliability professionals.
The history of reliability engineering
It might seem that engineering in general, and reliability engineering in particular, is a rather modern discipline. In fact, as soon as machines first became an integral part of human life, something that people depended on for survival, there also appeared the demand for machines to be reliable. Still, in ancient times engineering practices were not very advanced for obvious reasons.
Modern reliability engineering started to rapidly develop after the Second World War. This technical discipline as we see it today grew as a result of a significant increase in commercial aviation numbers which, in turn, made the aviation industry very motivated to reduce the failure rates of mechanical equipment that often led to horrible accidents.
The military also played an important role in improving reliability methods. Since military equipment is considered critical for defense, its working state was ensured by reliability engineering techniques. Multiple reliability engineering principles that are considered standard today originate from activities designed by the military.
Why failures occur
To understand how reliability engineers prevent failures, it is important to take a closer look at why failures occur in the first place. Learning more about failure mechanisms can help us pinpoint certain factors that are crucial for reliability prediction. Such factors can then be taken into consideration when implementing the best engineering practices in your reliability engineering activities.
Product design
The very core of your product or system, the way it is designed, can cause a decrease in its likely reliability. This is especially true for more complex systems where multiple components depend on each other. Each aspect of each component has the potential to become a hazard if it is designed incorrectly and, for example, requires too many resources or relies on outdated libraries.
Stress
Failures occur when the amount of stress applied is higher than the ability of a certain component to withstand it. Stress doesn't necessarily mean just literal physical pressure. For example, the software you build is put under more load than it is designed to handle, leading to a failure. A good example is the “Fail Whale”. In the early days of Twitter, the platform was often overwhelmed by the number of tweets and connections during high-traffic events, such as sports games, political events, or popular TV shows. The system's capacity was not designed to handle such high volumes of data and connections, and as a result, the website and app would crash, showing an image of a whale being lifted by birds, known as the "Fail Whale".
The designers of any product typically strive to ensure a margin between the maximum stress that can be applied and the strength of the component, but it is just not possible to cover all the cases where stress could exceed the limits. Over-stressed components will eventually become failed components, no matter what kind of protection is in place.
Time
Often a system or a product can function reliably at the beginning of its life cycle but with time wear and tear will negatively impact its functionality. The wear becomes especially noticeable when other environmental factors are also in play.
From a software development standpoint, time-induced failures might be:
- Software aging and degradation: Just like physical systems, software systems can also "age". Over time, software may start to perform poorly or even fail due to various factors such as memory leaks, data corruption, or resource leaks. These are issues that accumulate over time and are not immediately apparent. As an example, a long-running server application might gradually consume more and more memory due to a small memory leak, eventually leading to a system crash or significant slowdown.
- Obsolescence: Software often becomes outdated over time as new technologies, standards, and best practices emerge. This can lead to compatibility issues and decreased performance. For instance, a web application developed years ago might not work properly on modern web browsers due to changes in standards and technologies.
- Dependency failures: Software systems often depend on external systems or services, and these dependencies can lead to time-induced failures. For example, if software relies on an API that changes or is deprecated, the software may stop functioning correctly unless it is updated. Similarly, if software relies on a third-party service that experiences downtime, it can cause the dependent software to fail.
- Operational load and stress over time: As the user base or data volume of an application grows over time, the system might start to struggle if it has not been designed to scale effectively. For example, a database that worked fine in the early days of a startup may start to fail under the load of millions of users or records, causing application failures or significant performance issues.
- Software decay: If a software component is not maintained, its quality can degrade over time, leading to what is known as software decay. Bugs may become more apparent, performance may decline, and security vulnerabilities may be exposed. An example might be an old library that's used in the system which has not been updated or patched for a long time, and over time, it becomes a source of failure.
Errors
Any product life cycle contains multiple stages, and at each of these stages something can go wrong and remain unnoticed. Errors can occur early, during the design stage, or are missed during testing. The software coding or specifications could contain errors. Or, everything could be designed perfectly but incorrect maintenance could lead to maintenance-induced failures. The end user could also just implement the product incorrectly, which can also easily become a cause of errors.
Sneaks
There are certain design conditions that are harder to detect with traditional testing and analysis procedures. These so-called sneaks can significantly impact the reliability of a system or software. Basically, a sneak means that a failure can occur only under very specific conditions because of the way the product functions. For a sneak to happen, usually, a specific sequence of actions needs to be performed. A modern software or network-related example could be related to race conditions or concurrency issues. These problems are often hard to detect because they depend on very specific timing conditions that may not occur during regular testing.
Failure mechanisms and failure modes
Although sometimes the cause of the failure can be detected easily, that is not always the case. One of the most important parts of a reliability engineer’s work is determining failure mechanisms and addressing failure modes. These two terms are sometimes used interchangeably but there is a clear difference.
A failure mechanism is a deviant state or condition of a system or a component that is a direct cause of failure. A failure mode is the result of the failure mechanism existing, it is an event that is characterized by abnormal functioning or behavior.
Reliability engineering tools and techniques
The exact scope of the work for a reliability engineer depends on the industry, of course. Still, it is possible to outline several groups of reliability engineering methods, tools, and techniques that can be considered the basis of reliability engineering.
Planning
Some reliability engineering methods are not specific only to this subfield of engineering. It is a standard practice to review and organize resources that are available for a specific project to make sure you are ready to determine and fix any issues connected to reliability.
Reliability programs are a way to organize reliability activities across the organization. When you create a reliability program, it makes it easier to detail and support everything required for effective monitoring, oversight, and other activities that ensure reliability for every project.
The tools that are typically used on the level of reliability programs include reliability training, data collection and analysis, reporting, and so on. Reliability assessment, which can be done with a very wide range of tools, from complex software to a simple sheet of paper, is also typically performed as a part of a reliability program.
You can also create reliability projects if it is necessary to focus on the manufacturing or development of a specific component or product, but there might be a certain overlap between reliability programs and projects depending on the organization. It is important to remember though, that a reliability project is a more formal approach, and depending on circumstances you might just need a more efficient assessment of your product reliability.
Risk analysis
Looking for failures before they even happen, that is, analyzing the risk of failures occurring, is a big part of what reliability engineers do. The standard tools for this include, for example, failure mode and effect analysis (FMEA) which helps discover potential weak spots in components and then also to see how these failure modes might impact the rest of the product. If the analysis also involves quantifying the risk level of the discovered failure modes then this tool is named failure mode effects and criticality analysis (FMECA).
Highly accelerated life testing (HALT) is a stress testing methodology used to discover potential defects and weaknesses in products, typically applied to hardware products. The principle is to stress a system beyond its specified limits to identify weaknesses and failure points.
While HALT has its roots in hardware testing, principles from HALT can also be applied in the realm of software development by simulating prolonged exposure to normal or abnormal use.
Risk analysis techniques also include prototype failure analysis, simulations, beta testing, and other methods that help determine reliability risks that might occur over a specified period of time.
We have a whole article about risk management – check it out to be prepared for various types of software development risks.
Incorporating reliability
We have already mentioned that the system or product design itself can cause failures. That is why there is a set of tools that reliability engineers use to incorporate reliability into the very product itself. It might involve, for example, stress-strength analysis or derating, which involves selecting libraries and components in accordance with a set of safety-margin standards, to ensure the technologies you use for the product are the best for the specific conditions in which it is going to function.
Reliability modeling is crucial as well. There are several popular techniques that allow you to confirm that selected components or tools will meet specific environmental or use conditions. One of them is using reliability block diagrams. This mathematical and graphical model helps you to calculate a system's reliability, taking into account the reliability of its separate components.
Fault tree analysis is another widely used method. This technique involves creating a logical diagram that outlines multiple possible paths that describe the cause and effect of a certain failure mode.
Reliability statistics and statistical analysis are crucial for reliability engineering in software development, and statistical tools can be used at every stage of the software life cycle. This is especially important during the design and development stage. You can use statistical analysis to evaluate various factors such as code complexity, user behavior patterns, dependency reliability, and server load conditions. Additionally, statistical methods can help understand how these factors might change under different usage scenarios and deployment environments, thereby aiding in creating more robust and reliable software.
Performance estimate
Predicting the future might seem an impossible thing to do but reliability engineers use all the available qualitative and quantitative evidence to estimate the performance of a component or a system in the future, once it starts working. The tools that help to make a reliability prediction regarding future performance include field data from similar products, reliability life-like testing or alpha and beta testing, and even, quite simply, engineering judgment. Sometimes all that quantifying reliability takes is an educated guess from an experienced reliability engineer.
Reliability block diagrams or a similar modeling technique can be used for this purpose as well, to estimate performance reliability for each subcomponent or subsystem separately.
Failure analysis
One more set of tools that reliability engineers use regularly deals with the failures that do happen after all. The most widely used tool here is perhaps root cause analysis but it represents just one part of the comprehensive failure analysis process.
Analyzing the historical data from maintenance processes and failure data also helps with failure measurement and identification. Sometimes maintenance practices themselves could be the cause of failures so it is important to make sure the analysis can also discover reliability hazards relating to maintenance.
Comprehensive tools like failure reporting and corrective systems (FRACAS) can guide you all the way from failure discovery to a successful resolution. It provides a process for reporting, classifying, and analyzing failures, and planning corrective actions in response to those failures. It's commonly used in traditional engineering fields but can also be applied to software development.
The importance of reliability engineering – summary
Reliability engineering is fairly different from traditional quality control as it involves looking into the future and predicting how the system or product will behave in real-life conditions. There are quite a few benefits though, that you can get from effective reliability engineering on your project.
Since reliability engineering deals with preventing failures, the resulting product works according to the customers' expectations. Warranty periods and SLAs (service level agreements) become something that your end users can really trust. All this makes your customers happy and reduces the costs that originate from providing warranty service and product returns.
Generating reliable products also means you can better anticipate the failures that do happen and fix them quicker. Reliable systems are safer because reliability engineering helps you to identify risks that could lead to the loss of property or even the health of an individual and mitigate them effectively.
Even though some statistical models used in reliability engineering might seem overly complicated, these days there are many kinds of software that can help with every step of reliability management in your organization. Reliability prediction, life data analysis, and even reliability-centered maintenance can be often automated and all the data collected and visualized in convenient charts to facilitate continuous improvement.
Investing in reliability engineering is a way to efficiently organize the quality management of your product and make your customers happy, not only on the day of purchase but during the whole product lifespan.
