Determination of System and Component Reliability Parameters

Component and System Requirements are specified using reliability parameters. Although, the most common existing reliability parameter is the mean-time-between-failure, (MTBF), which can also be specified as the failure rate or the number of failures during a given period. These parameters are very useful for systems that are operating on a regular basis, such as most vehicles, machinery, and electronic equipment. Reliability increases as MTBF increases. The MTBF is usually specified in hours, but can be used as the probability of mission success. For example, reliability of a scheduled aircraft can be specified as a dimensionless probability or percentage. In the so-called zero defect experiments, only limited information about the failure distribution is acquired. Here the stress, stress time, or the sample size is so low that not a single failure occurs. Due to insufficient sample size, only an upper limit of the early failure rate can be determined. At any rate, it looks good for the customer if there are no failures. In a study of intrinsic failure distribution, which is often a material property, higher stresses are necessary to get failure in a reasonable period of time. Several degree of stress has to be applied to determine an acceleration model. The empirical failure distribution is often parameterized with a Weibull or a log-normal model. It is generally done to model, where the early failure rate has an exponential distribution. This less complex type of model for the failure distribution has only one parameter - the constant failure rate. Due to the fact that, reliability is a probability, even highly reliable systems have some chance of failure. However, existing methods of testing reliability requirements are problematic for several reasons. A single test is insufficient to generate enough statistical data. Multiple tests or long-duration tests are usually very expensive. Some tests are simply impractical. Reliability engineering is used to design a realistic and affordable test program that provides enough evidence that the system meets its requirement. Statistical confidence levels are used to address some of these concerns. Care is therefore needed to select the best combination of requirements. An integrated reliability model testing that can perform at various levels, such as component, subsystem, and system as well as such that can address many factors during testing, such as extreme temperature and humidity, shock, vibration, and heat is highly essential for the different industries. Integrated reliability model with technological inheritance coefficients can be applied for effective test strategy at all levels of design, development and operations so that all parts are exercised in relevant environments. The benefits of integrated reliability model testing for design, operations and maintenance of components and systems in the different environments with the help of technological inheritance coefficients will be discussed in the subsequent blogs of this site.