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Single point of failure. In this diagram the router is a single point of failure for the communication network between computers. A single point of failure (SPOF) is a part of a system that, if it fails, will stop the entire system from working. [1] SPOFs are undesirable in any system with a goal of high availability or reliability, be it a ...
FMEA is an inductive reasoning (forward logic) single point of failure analysis and is a core task in reliability engineering, safety engineering and quality engineering. A successful FMEA activity helps identify potential failure modes based on experience with similar products and processes—or based on common physics of failure logic.
Some genetic diseases are named more precisely, and represent a single point of failure on a metabolic pathway. For example, Tay–Sachs disease, GM2-gangliosidosis, AB variant, and Sandhoff disease might easily have been defined together as a single disease, because the three disorders are associated with failure of the same enzyme and have ...
Fault tolerance is the ability of a system to maintain proper operation despite failures or faults in one or more of its components. This capability is essential for high-availability, mission-critical, or even life-critical systems. Fault tolerance specifically refers to a system's capability to handle faults without any degradation or downtime.
The Swiss cheese model of accident causation is a model used in risk analysis and risk management. It likens human systems to multiple slices of Swiss cheese, which has randomly placed and sized holes in each slice, stacked side by side, in which the risk of a threat becoming a reality is mitigated by the differing layers and types of defenses ...
Event tree analysis (ETA) is a forward, top-down, logical modeling technique for both success and failure that explores responses through a single initiating event and lays a path for assessing probabilities of the outcomes and overall system analysis. [1] This analysis technique is used to analyze the effects of functioning or failed systems ...
The first piece of information added in an FMEDA is the quantitative failure data (failure rates and the distribution of failure modes) for all components being analyzed. The second piece of information added to an FMEDA is the probability of the system or subsystem to detect internal failures via automatic on-line diagnostics.
Common and special causes are the two distinct origins of variation in a process, as defined in the statistical thinking and methods of Walter A. Shewhart and W. Edwards Deming. Briefly, "common causes", also called natural patterns, are the usual, historical, quantifiable variation in a system, while "special causes" are unusual, not ...