China
Africa
Explore chapters and articles related to this topic
Evaluating Platform Reliability and Measuring Its Dollar Value
Published in Steven F. Blanding, Enterprise Operations Management, 2020
Vendors of failover systems assert that almost everyone can live with a few minutes of downtime per year. This may be true for some businesses, but downtime in failover systems is actually much longer than a few minutes. Tandem Computers has developed a client/server availability model that can be used to predict downtime. It is available on the World Wide Web: http://www.tandem.com/prod/nsa/. The model uses a representative client/server environment containing 1000 clients, 20 hubs, 6 routers, 40 database servers, and 1 network management server. For non-fault-tolerant systems, the predicted annual downtime is approximately 12,000 minutes, or 200 hours per client, which translates to 97.7 percent availability. For configurations of fault-tolerant systems and networks, the predicted annual downtime is 59 hours per client, or 99.3 percent availability. Fifty-nine hours for each client is significantly more than “a few minutes.”
Reliability Measures and Indices for Amusement Park Rides
Published in Vonta Ilia, Ram Mangey, Reliability Engineering, 2019
Stavros Kioutsoukoustas, Alex Karagrigoriou, Ilia Vonta
Table 7.1 provides the relationship between the three main concepts of reliability theory. From the table, we easily deduce that: A constant reliability does not necessarily imply high availability.A constant reliability (even a low one) could imply high availability provided the maintainability increases (i.e., the time for maintenance decreases).If maintainability decreases (i.e., the time for maintenance increases), the availability also decreases.
Communications Systems
Published in Stuart Borlase, Smart Grids, 2018
Mehrdad Mesbah, Sharon S. Allan, Donivon D. Hettich, Harry Forbes, James P. Hanley, Régis Hourdouillie, Marco C. Janssen, Henry Jones, Art Maria, Mehrdad Mesbah, Rita Mix, Jean-Charles Tournier, Eric Woychik, Alex Zheng
Communications system availability is another consideration. System availability is defined as the amount of uptime, measured in a percentage, that a network can communicate to a given device population. A system that is up 99.9% of the time is stated to have 3 NINEs of availability, which amounts to over 500 min of system downtime per year. A system with 5 NINEs of availability has just over 5 min of downtime per year. Communication system downtime occurs for both unscheduled (system impairments), and scheduled (upgrade and configuration changes) outages. Self-healing and protection communication systems require less downtime due to the critical functionality they provide. It is noted that in most scenarios, grid optimization applications require only 2 to 3 NINEs of availability per year.
Reliability Analysis of Microgrids: Evaluation of Centralized and Decentralized Control Approaches
Published in Electric Power Components and Systems, 2023
Selahattin Garip, Melih Bilgen, Necmi Altin, Saban Ozdemir, Ibrahim Sefa
Reliability refers to the ability of a system or product to perform its intended function without failure, interruption, or error over a predetermined duration, or within a specific timeframe and under specified operating conditions. Reliability can be quantified by various metrics, such as mean time between failures (MTBF), failure rate, and availability. MTBF represents the average time between two consecutive failures of a system or product, while failure rate represents the probability of a failure occurring within a given time period. Availability represents the percentage of time that a system or product is operational and ready to perform its intended function. In engineering and industry, reliability is a critical factor in the design, testing, and production of various systems and products, including electrical systems, mechanical systems, software, and complex machinery. High reliability is often a requirement for mission-critical systems, such as those used in aerospace, defense, transportation, and medical applications, where failure can have severe consequences.
Modularisation of system architecture to improve system recoverability: a unique application of design structure matrix
Published in Journal of Engineering Design, 2021
Ali Mollajan, Seyed Hossein Iranmanesh
‘Reliability’, ‘Availability’ and ‘Recoverability’ is a set of related attributes that should be considered when designing a system (ASQ 2011). Hence, delineation of these concepts may be useful. Availability is defined as the probability that a restorable system or system element is operational at a given point in time under a given set of environmental conditions and depends on reliability and recoverability (ASQ 2011). Reliability is defined as the probability of a system or system element performing its intended function under stated conditions without failure for a given period of time (Sarkar 2016). Therefore, reliability measures the ability of a system to function correctly whereas availability measures how often the system is available for use, even though it may not be functioning correctly (Roy, Ganesan, and and Sarkar 2013).
Availability function as bridge element’s importance weight in computing overall bridge health index
Published in Structure and Infrastructure Engineering, 2018
Sylvester Inkoom, John Sobanjo
Availability is an essential metric for evaluating the system performance that accounts for both the reliability and maintainability properties of an element, subsystem or the entire system (Frankel, 2013; Leemis, 1995; Wang, Loman, & Vassiliou, 2004). The purpose of using the availability as importance measure for bridge elements is that the metric evaluates the available capacity of system components (which could be described as residual strength of components) while the unavailable capacity estimates the inherent failure requirement. Availability, in terms of the duration the element is functioning (Uptime) and the time the element is down (Downtime) (Goldsim, 2014), is computed as: where =Average time to failure; and =Average time to repair.