Assessing Product Reliability
|A reliability improvement test is a formal procedure aimed at discovering and fixing system reliability flaws||During the early stages of
developing and prototyping complex systems, reliability often does not
meet customer requirements. A formal test procedure aimed at discovering
and fixing causes of unreliability is known as a Reliability Improvement
Test. This test focuses on system design, system assembly and component
selection weaknesses that cause failures.
A typical reliability improvement test procedure would be to run a prototype system, as the customer might for a period of several weeks, while a multidisciplined team of engineers and technicians (design, quality, reliability, manufacturing, etc.) analyze every failure that occurs. This team comes up with root causes for the failures and develops design and/or assembly improvements to hopefully eliminate or reduce the future occurrence of that type of failure. As the testing continues, the improvements the team comes up with are incorporated into the prototype, so it is expected that reliability will improve during the course of the test.
|Repair rates should show an improvement trend during the course of a reliability improvement test and this can be modeled using a NHPP model||Another name for reliability improvement testing is TAAF
testing, standing for Test, Analyze And Fix.
While only one model applies when a repairable system has no improvement or degradation trends (the constant repair rate HPP model), there are infinitely many models that could be used to describe a system with a decreasing repair rate (reliability growth models).
Fortunately, one or two relatively simple models have been very successful in a wide range of industrial applications. Two models that have previously been described will be used in this section. These models are the NHPP Power Law Model and the NHPP Exponential Law Model. The Power Law Model underlies the frequently used graphical technique known as Duane Plotting.