A reliability analyst conducts evaluations on products, tests, surveys, and processes to determine if they provide consistent results and can be considered reliable. The importance of reliability analysis cannot be understated because it is impossible to determine if a product meets all functionality and safety expectations without consistent tools for measuring results.
Reliability is the measurement of how consistent a measurement is or how easy it is to repeat. When preparing new tests and methods of analysis, you want to see consistent results. In short, the test or study needs to be consistent. Otherwise, it can be impossible to compare the results of various sets of data. If the amount of space in an inch changed every time you used a tape measure, the results would be meaningless. Reliability, however, is different from validity, which looks at how accurate measurements are. If measurements are off, a product test can indicate reliability while returning data that is not valid. Likewise, test results can be valid but not reliable because they cannot be reproduced consistently.
Internal and External Reliability
You can split reliability into two categories. Internal reliability looks at how consistent a measurement is as it applies to what it’s testing. For example, if you put several metal supports through the same durability test with the same conditions, and none of them buckle until several thousand pounds of pressure are put on them, those supports are internally reliable. If these supports are then put through various durability tests and perform similarly, they are externally reliable.
How is Reliability Assessed?
There are four different ways you can test reliability. These approaches can be made individually, or you can use several of these tests to fully determine how reliable a product is. Some are designed to measure internal reliability, while other methods look at external reliability. You will typically want to assess both.
Internal consistency takes several products and looks to see if the results of tests are consistent across the entire batch. This is often the first internal reliability assessment. When a product fails an internal consistency review, the issue may lie with the materials used in the product or with the manufacturing process. There may be unknown variables introduced in either that result or in a series of inconsistent products.
You can use the split-half method for internal reliability. This method splits the data results into two groups and compares them to each other. Data can be grouped in various ways, allowing you to perform multiple split-half analyses to confirm reliability. Again, you can use this to look for consistency in production, but you can also use it to determine if your testing measures include errors or tester bias.
Inter-rater reliability, an external test, compares the results different raters or testers get. This type of testing aims to determine if there is any rater influence and, if so, how it affects the testing of the product. You can use inter-rater reliability to adjust your testing methods or the methods used to measure results.
A test re-test assessment tests the product multiple times over a period of time. This test determines if environmental factors or other factors that may change over time affect the product’s reliability. This is also an external assessment method because it can look at how products are affected by different lengths of time and different environments. When a product fails a test re-test assessment, you will need to determine if the product requires a redesign, if the materials used need to change, or if the environment the product was exposed to will not be a concern. If a product design does not work in a specific environment, failing a test re-test assessment for that environment may be inconsequential.
Why Perform Reliability Analysis?
There are many reasons why you need to perform a reliability analysis on a product, a testing method, a survey, and other tools. Let’s take a look at some of these reasons and highlight the importance of reliability analysis.
It Shows Products Will Return Valid Results Under Various Conditions
Testing a product once may return results that appear valid. Still, without multiple external reliability tests, you cannot be sure that it will function as intended in various environments and situations. This includes different temperatures, altitudes, humidity levels, stress, among other factors. By performing reliability tests in all potential conditions in which the product will perform, you can be sure the product is functioning as intended.
One such reliability analysis example involves a critical component on an aircraft. This component may perform well at altitudes, which is one of the obvious factors to test. However, humidity could result in performance issues. If you don’t test at various humidity levels, you may never discover this weakness because you may do all other tests at the same humidity.
Reliability analysis also indicates if a product will return valid results over a period of time. Some products may perform as expected shortly after being installed, but time can wear them down. Even products that are not in use may still be affected by the passage of time, leaving them weaker or otherwise unable to function as they should. Testing in multiple environments over time provides an opportunity to gradually see how various conditions affect parts and products. For example, testing a product near the ocean over several months will show how it reacts to saltwater exposure.
Reliability Testing Assures Consistency
Internal reliability analysis assures products act consistently when put through the same testing environment multiple times. This is a necessity in engineering when components must perform identically every time. If they fail this reliability test, you cannot trust the products to perform their necessary functions. This can create safety risks and could result in the loss of millions of dollars or users’ lives. Even if that is not the case, inconsistent products can affect sales and lead to a loss of profits.
It Removes Tester Bias and Accounts for Human Error
Product testers, quality assurance teams, and others who test products before they are mass-produced may often have unconscious bias. They may not intentionally perform testing with bias, but everyone has assumptions and automatic responses to things that may fail to consider other points of view. Inter-rater reliability testing attempts to isolate these assumptions and biases by having multiple testers conduct tests. This also highlights testers’ assumptions during their evaluations and can bring to light some judgments individual testers made that may not necessarily be correct.
Human error is another issue with product testing. If only one user or one team of testers test the product, the process may be tainted by human error. This can lead to results that do appear to be valid but are not, regardless of their consistency or inconsistency. Some products tested using a process containing errors may appear reliable when they aren’t or vice versa. Testing multiple times by multiple testers can account for any human errors added to the testing process, ensuring a reliable product.
It Evaluates Data Gathering Tools and Testing Measures
You can also use reliability analysis to evaluate the tools used to gather data and measure test results. As mentioned earlier in one example, data collected from a measuring tape would be useless if the distance between inches was not the same each time. You can do reliability analysis on surveys and other data collection methods to ensure that the results that come in are consistent and can be measured against each other. If these tools return data that is too varied in its structure, that data may not be comparable or able to be grouped in any meaningful way.
This is another way of testing your testing measures. You can use the split-half method and test re-test method to determine if the methods you are using to analyze your data are working as intended. This is another area where many people blindly move forward in product development without considering if the way they are evaluating test results is correct. Incorrect testing measurements can return results that appear both reliable and valid when, in fact, they are not. This could then lead to products being made widely available with internal defects or that do not perform as expected in certain conditions.
Reliability Analysis is Vital to Engineering
As you can see, implementing reliability analysis in engineering is vital. It allows designers and manufacturers to ensure that the components used in any products, structures, and other ways are dependable and will perform as intended in a wide variety of scenarios. Reliability engineering has become a vital part of the design and testing process and should be included in all product design cycles.