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Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability is defined as the probability that a product, system, or service will perform its intended function adequately for a specified period of time, OR will operate in a defined environment without failure. [1]
There are three principles of systems design in reliability engineering that can help achieve high availability. Elimination of single points of failure. This means adding or building redundancy into the system so that failure of a component does not mean failure of the entire system. Reliable crossover.
For databases reliability, availability, scalability and recoverability (RASR), is an important concept. Atomicity, consistency, isolation (sometimes integrity), durability is a transaction metric. When dealing with safety-critical systems, the acronym reliability, availability, maintainability and safety is frequently used.
High reliability organization theory and HROs are often contrasted against Charles Perrow's Normal Accident Theory [5] (see Sagan [6] for a comparison of HRO and NAT). NAT represents Perrow's attempt to translate his understanding of the disaster at Three Mile Island nuclear facility into a more general formulation of accidents and disasters.
Semiconductor Design for Manufacturing (DFM) Semiconductor Design for Manufacturing (DFM) is a comprehensive set of principles and techniques used in integrated circuit (IC) design to ensure that those designs transition smoothly into high-volume manufacturing with optimal yield and reliability. DFM focuses on anticipating potential fabrication ...
In engineering, reliability, availability, maintainability and safety (RAMS) [1] [2] is used to characterize a product or system: Reliability: Ability to perform a specific function and may be given as design reliability or operational reliability; Availability: Ability to keep a functioning state in the given environment
The cleanroom software engineering process is a software development process intended to produce software with a certifiable level of reliability. The central principles are software development based on formal methods, incremental implementation under statistical quality control, and statistically sound testing.
The probabilistic design principles allow for precise determination of failure probability, whereas the classical model assumes absolutely no failure before yield strength. [9] It is clear that the classical applied load vs. yield stress model has limitations, so modeling these variables with a probability distribution to calculate failure ...