A new reliability engineering search tool was recently added to the Reliability Analytics Toolkit. This tool indexes, on a page level basis, approximately 30,000 pages from various reliability engineering “standards” (government standards, handbooks, guides and reports related to reliability, maintainability, availability, safety, etc.). The tool provides a more comprehensive search capability than the Google Custom Search box at the top of each page, which only outputs pages ranked high by Google, but not necessarily all pages that contain a particular set of words. Continue reading
The reliability functions of some simple, well known structures will be derived. These functions are based upon the exponential distribution of time to failure.
The simplest and perhaps most commonly occurring configuration in reliability mathematical modeling is the series configuration. The successful operation of the system depends on the proper functioning of all the system components. A component failure represents total system failure. A series reliability configuration is represented by the block diagram as shown below with n components.
Figure 1 shows a typical time versus failure rate curve for equipment. This is the well known “bathtub curve,” which, over the years, has become widely accepted by the reliability community.
It has proven to be particularly appropriate for electronic equipment and systems. Note that it displays the three failure rate patterns, a decreasing failure rate (DFR), constant failure rate (CFR), and an increasing failure rate (IFR).
Failure modeling is a key to reliability engineering. Validated failure rate models are essential to the development of prediction techniques, allocation procedures, design and analysis methodologies, test and demonstration procedures, control procedures, etc. In other words, all of the elements needed as inputs for sound decisions to insure that an item can be designed and manufactured so that it will perform satisfactorily and economically over its useful life.
Inputs to failure rate models are operational field data, test data, engineering judgment, and physical failure information. These inputs are used by the reliability engineer to construct and validate statistical failure rate models (usually having one of the distributional forms described previously) and to estimate their parameters.