Introduction to Accelerated Life Testing

Introduction

Foreword

This reference has been designed to accompany ReliaSoft's Accelerated Life Test Analysis software packages, ALTA 7 Standard and ALTA 7 PRO. The treatment of the subject and most of the examples included in this reference assume that the reader has installed and can refer to the ALTA 7 software.

The purpose of this <index>Reference Purposereference is to provide the reader with a general overview of the subject of accelerated life testing data analysis as it applies to the use of the ALTA package. It includes the underlying theory and principles, relevant calculations and derivations, and numerous practical examples and case studies.

Modifications and Enhancements

This reference has been updated and enhanced since the last major printing to include a discussion of the principles and theory behind the new functionality available in ALTA 7 and ALTA 7 PRO. This includes changes to mathematical derivations of Maximum Likelihood Estimates (MLE) solutions to include interval data. This reference also includes an additional life-stress model: generalized Eyring model. A presentation of the principles and theory that support a new supplementary analysis tool, Accelerated Life Test Plans, is also included. A more detailed discussion of the cumulative damage model, with different distributions and transformations in addition to added ability to analyze data with multiple time-varying stress types, has also been added to this reference. This sophisticated cumulative damage model has been highly anticipated in the reliability engineering field and its development is the result of extensive research efforts.

About this Reference

This reference is one in a series of reliability engineering reference works created by ReliaSoft. Some concepts and examples related to life data analysis that have been extensively covered in ReliaSoft's Life Data Analysis Reference have been omitted from this reference. ReliaSoft maintains on-line versions of these documents on its Weibull.com site, and the reader is encouraged to refer to the on-line documents for the most recent updates.

What is Accelerated Life Testing?

Foreword

Traditional life data analysis involves analyzing times-to-failure data (of a product, system or component) obtained under normal operating conditions in order to quantify the life characteristics of the product, system or component. In many situations, and for many reasons, such life data (or times-to-failure data) is very difficult, if not impossible, to obtain. The reasons for this difficulty can include the long life times of today's products, the small time period between design and release, and the challenge of testing products that are used continuously under normal conditions. Given this difficulty, and the need to observe failures of products to better understand their failure modes and their life characteristics, reliability practitioners have attempted to devise methods to force these products to fail more quickly than they would under normal use conditions. In other words, they have attempted to accelerate their failures. Over the years, the term Accelerated Life Testing has been used to describe all such practices. A variety of methods that serve different purposes have been termed accelerated life testing. As we use the term in this reference, accelerated life testing involves acceleration of failures with the single purpose of quantification of the life characteristics of the product at normal use conditions. More specifically, accelerated life testing can be divided into two areas: qualitative accelerated testing and quantitative accelerated life testing. In qualitative accelerated testing, the engineer is mostly interested in identifying failures and failure modes without attempting to make any predictions as to the product's life under normal use conditions. In quantitative accelerated life testing, the engineer is interested in predicting the life of the product (or more specifically, life characteristics such as MTTF, B(10) life, etc.) at normal use conditions, from data obtained in an accelerated life test.

Types of Accelerated Tests

Each type of test that has been called an accelerated test provides different information about the product and its failure mechanisms. These tests can be divided into two types: Qualitative Tests (HALT, HAST, Torture Tests, Shake and Bake Tests, etc.) and Quantitative Accelerated Life Tests. This reference addresses and quantifies the models and procedures associated with quantitative accelerated life tests (QALT).

Qualitative Accelerated Testing

Qualitative tests are tests which yield failure information (or failure modes) only. They have been referred to by many names including:
• Elephant Tests • Torture Tests • HALT • Shake & Bake Tests

Qualitative tests are performed on small samples with the specimens subjected to a single severe level of stress, to a number of stresses, or to a time-varying stress (i.e. stress cycling, cold to hot, etc.). If the specimen survives, it passes the test. Otherwise, appropriate actions will be taken to improve the product's design in order to eliminate the cause(s) of failure. Qualitative tests are used primarily to reveal probable failure modes. However, if not designed properly, they may cause the product to fail due to modes that would never have been encountered in real life. A good qualitative test is one that quickly reveals those failure modes that will occur during the life of the product under normal use conditions. In general, qualitative tests are not designed to yield life data that can be used in subsequent quantitative accelerated life data analysis as described in this reference. In general, qualitative tests do not quantify the life (or reliability) characteristics of the product under normal use conditions, however they provide valuable information as to the types and levels of stresses one may wish to employ during a subsequent quantitative test.

Benefits and Drawbacks of Qualitative Tests

• Benefit: Increase reliability by revealing probable failure modes. • Provide valuable feedback in designing quantitative tests, and in many cases they are a precursor to a quantitative test. • Unanswered Question: What is the reliability of the product at normal use conditions?

Quantitative Accelerated Life Testing

Quantitative Accelerated Life Testing (QALT), unlike the qualitative testing methods described previously, consists of tests designed to quantify the life characteristics of the product, component or system under normal use conditions, and thereby provide reliability information. Reliability information can include the determination of the probability of failure of the product under use conditions, mean life under use conditions, and projected returns and warranty costs. It can also be used to assist in the performance of risk assessments, design comparisons, etc.

Quantitative accelerated life testing can take the form of Usage Rate Acceleration or Overstress Acceleration. Both accelerated life test methods are described next. Because Usage Rate Acceleration test data can be analyzed with typical life data analysis methods, the Overstress Acceleration method is the testing method relevant to both ALTA and the remainder of this reference.

Quantitative Accelerated Life Tests

For all life tests, some time-to-failure information (or time-to-an-event) for the product is required since the failure of the product is the event we want to understand. In other words, if we wish to understand, measure, and predict any event, we must observe how that event occurs!

Most products, components or systems are expected to perform their functions successfully for long periods of time, such as years. Obviously, for a company to remain competitive, the time required to obtain times-to-failure data must be considerably less than the expected life of the product. Two methods of acceleration, Usage Rate Acceleration and Overstress Acceleration, have been devised to obtain times-to-failure data at an accelerated pace. For products that do not operate continuously, one can accelerate the time it takes to induce/observe failures by continuously testing these products. This is called Usage Rate Acceleration. For products for which Usage Rate Acceleration is impractical, one can apply stress(es) at levels which exceed the levels that a product will encounter under normal use conditions and use the times-to-failure data obtained in this manner to extrapolate to use conditions. This is called Overstress Acceleration.

Usage Rate Acceleration

For products which do not operate continuously under normal conditions, if the test units are operated continuously, failures are encountered earlier than if the units were tested at normal usage. For example, a microwave oven operates for small periods of time every day. One can accelerate a test on microwave ovens by operating them more frequently until failure. The same could be said of washers. If we assume an average washer use of 6 hours a week, one could conceivably reduce the testing time 28-fold by testing these washers continuously.

Data obtained through usage acceleration can be analyzed with the same methods used to analyze regular times-to-failure data. These typical life data analysis techniques are thoroughly described in ReliaSoft's Life Data Analysis Reference [31] and facilitated by ReliaSoft's Weibull++ software package (http://Weibull.ReliaSoft.com).
The limitation of Usage Rate Acceleration arises when products, such as computer servers and peripherals, maintain a very high or even continuous usage. In such cases, usage acceleration, even though desirable, is not a feasible alternative. In these cases the practitioner must stimulate, usually through the application of stress(es), the product to fail. This method of accelerated life testing is called Overstress Acceleration and is described next.

Overstress Acceleration

For products with very high or continuous usage, the accelerated life testing practitioner must stimulate the product to fail in a life test. This is accomplished by applying stress(es) that exceed the stress(es) that a product will encounter under normal use conditions. The times-to-failure data obtained under these conditions are then used to extrapolate to use conditions. Accelerated life tests can be performed at high or low temperature, humidity, voltage, pressure, vibration, etc. in order to accelerate or stimulate the failure mechanisms. They can also be performed at a combination of these stresses.

Stresses & Stress Levels

Accelerated life test stresses and stress levels should be chosen so that they accelerate the failure modes under consideration but do not introduce failure modes that would never occur under use conditions. Normally, these stress levels will fall outside the product specification limits but inside the design limits as illustrated next:

Fig.1: Typical stress range for a component, product or system.

This choice of stresses and stress levels and the process of setting up the experiment is of the utmost importance. Consult your design engineer(s) and material scientist(s) to determine what stimuli (stresses) are appropriate as well as to identify the appropriate limits (or stress levels). If these stresses or limits are unknown, qualitative tests should be performed in order to ascertain the appropriate stress(es) and stress levels. Proper use of Design of Experiments (DOE) methodology is also crucial at this step. In addition to proper stress selection, the application of the stresses must be accomplished in some logical, controlled and quantifiable fashion. Accurate data on the stresses applied as well as the observed behavior of the test specimens must be maintained.

It is clear that as the stress used in an accelerated test becomes higher, the required test duration decreases. However, as the stress level moves farther away from the use conditions, the uncertainty in the extrapolation increases. Confidence intervals provide a measure of this uncertainty in extrapolation. (Confidence Intervals are presented in Appendix A of this reference.)

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