Ying Shi
Reliability Growth Testing [1]
Most often when the subject of reliability growth is discussed, it is reliability growth testing that is the focus of the discussion. Certainly, this focus on testing is neither surprising nor unreasonable. In general, testing, to prove the merit of a design and the validity of the models and analytical tools used to develop the design, is a necessary and standard part of development. In regard to reliability growth testing, much work has gone into developing the various statistical models developed for the purpose of planning and tracking reliability growth achieved through testing. Given the high cost of testing, the extensive effort to develop good models and the attention paid to the reliability growth test process are natural.
Coming out of the discussion as of whether reliability growth can be achieved without testing, generally speaking, the process is one of iteration. Iterations of the design are needed because the various performance requirements often conflict, optimizing the design to meet one requirement can result in the design failing to meet another requirement. Balancing the requirements is a demanding task. Iteration is also needed because not all analyses can be done simultaneously. consequently, the design may be changed as the result of a particular analysis, only to be changed again as the results of a subsequent analysis are available. As these iterations take place, the design is refined. Therefore, each revised design is an improvement over its predecessor. Some of the analyses conducted during the design process directly address the reliability of the design. So, the reliability of the design improves as successive design changes are made based on analytical evaluation.
Using the line of reasoning just presented, a broader definition of reliability growth could be developed : the process by which the reliability of an initial design is improved. Improvement can result as the design is iterated either on the basis of analytical evaluation and assessment or on test results. Ideally, when the product enters testing, all deficiencies have been eliminated through the design changes made as a result of analyses. So come up with this theory, the conclusion is that reliability growth does not have to be achieved with testing.
However, seldom is this ideal completely realized, and some design changes will be required as the result of design deficiencies discovered during development testing. And this is why a specific type of development testing often dedicated to the reliability growth process is brought up, the Reliability Growth Test.
Issues around reliability growth testing are coverage of test generation tool and testing results analysis specific to each type of testing.
As the trend during system development is the growing of system reliability, reliability growth models, each of them is tend to represent the growing trend, are acting as a guide help with measure and achieve this reliability growth resulting from improved software reliability and recovery algorithms. Many mathematical models exist nowadays, their basic working principle is to apply the testing results, data points, to the model, and based on the degree of matching or deviation from the model, judgment is made as of whether or not the system's development is coming towards reliability growth, and how much amount of refinement work need to be done right to this point of time.
The key that matters here with reliability growth model is how well each model represent the real system development process so that the refinement work done corresponding could really effectively and efficiently improve system reliability growth.
Duane showed a reliability engineering test process followed a predictable pattern, The underlying basis of this process is learning, in this case, redesign where there are unexpected failures. As with any physical process, randomness is to be expected. So our understanding from this is that the key issue for reliability growth model is the degree of its representing the system reliability growing trend. Now the fact is that more and more mathematical models come out, and tend to make those models more and more complex, which raises the question, is this diversity necessary. With the discussion going on, people show the preference of choosing simpler models.
Reliability Growth and Reliability Prediction[2]
As the concept of reliability growth has the in-born character of simplicity and easy understandability, it gets real popularly used. But this popularity also brings up the problem of improper applying of it in not a few cases and conditions, which make some of the researchers feel urgent to give it a clarification as of the use of this concept.
Conditions where reliability learning curve concept seems to fit:
models a single reliability development test activity; requires failure
analysis and corrective actions as part of test activity, and applies to
equipment that operates continuously.
Reasonable application of reliability learning curve:
Determine approximate reliability test time requirements; monitor rate of
reliability improvement in test
Unreasonable use of this curve:
Predicting equipment reliability, either current or future; used to combine
different types of reliability tests
The Objectives of Reliability Growth
The process of reliability growth has one primary objective - to improve the reliability of the design through analysis and test. The degree of possible improvement possible depends on the available resources, the underlying technology of the parts, components, and subsystems, and the knowledge of the design team.
Resources are always limited, so the reliability growth process must be as efficient as possible. A collateral objective of reliability testing, indeed, of all development testing, is to validate the models and tools used in creating the design.
The underlying technology is an obvious limiting factor in the degree of improvement possible in a design. Rather than relying on a continuous series of technological breakthroughs, design engineers must focus on the fundamentals and thoroughly understand the technologies at hand.
And the understanding of the design team is another constraint on the degree of improvement possible in the reliability, or any other performance characteristic, of a product. The models and tools used in creating a design reflect the current level of understanding of the technical community. To some extent, the models and tools are always inexact. By using test results to validate the models and tools and to revise or update them when we find they are not valid, our knowledge increases and the potential improvements possible for design increase.
Although
improvement of a design's reliability is the primary objective of the
reliability growth process, it is also an important means for improving our
models and tools used in creating a design. Reliability growth testing, one
aspect of the reliability growth process, is also being used to assess the
level of product reliability being achieved. This used of RGT creates a dilemma
for the developer. From the perspective of validating and understanding the
design, failures are welcome events. They present an opportunity for learning
and improvement. From the perspective of assessment, failures are not welcome.
To help deal with this dichotomy of purpose, the ground rules of all testing
must be well defined long before testing begins.