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'''Failure rate''' is the [[frequency]] with which an [[systems engineering|engineered system]] or component fails, expressed, for example, in failures per hour. It is often denoted by the [[Greek alphabet|Greek letter]] [[λ]] (lambda) and is important in [[reliability engineering]]. | |||
The failure rate of a system usually depends on time, with the rate varying over the life cycle of the system. For example, an automobile's failure rate in its fifth year of service may be many times greater than its failure rate during its first year of service. One does not expect to replace an exhaust pipe, overhaul the brakes, or have major [[Transmission (mechanics)|transmission]] problems in a new vehicle. | |||
In practice, the [[mean time between failures]] (MTBF, 1/λ) is often reported instead of the failure rate. This is valid and useful if the failure rate may be assumed constant – often used for complex units / systems, electronics – and is a general agreement in some reliability standards (Military and Aerospace). It does in this case ''only'' relate to the flat region of the [[bathtub curve]], also called the "useful life period". Because of this, it is incorrect to extrapolate MTBF to give an estimate of the service life time of a component, which will typically be much less than suggested by the MTBF due to the much higher failure rates in the "end-of-life wearout" part of the "bathtub curve". | |||
The reason for the preferred use for MTBF numbers is that the use of large positive numbers (such as 2000 hours) is more intuitive and easier to remember than very small numbers (such as 0.0005 per hour). | |||
The MTBF is an important system parameter in systems where failure rate needs to be managed, in particular for safety systems. The MTBF appears frequently in the [[engineering]] design requirements, and governs frequency of required system maintenance and inspections. In special processes called [[renewal process]]es, where the time to recover from failure can be neglected and the likelihood of failure remains constant with respect to time, the failure rate is simply the multiplicative inverse of the MTBF (1/λ). | |||
A similar ratio used in the [[transport industry|transport industries]], especially in [[railway]]s and [[Truck driver|trucking]] is "mean distance between failures", a variation which attempts to [[Correlation|correlate]] actual loaded distances to similar reliability needs and practices. | |||
Failure rates are important factors in the insurance, finance, commerce and regulatory industries and fundamental to the design of safe systems in a wide variety of applications. | |||
== | ==Failure rate in the discrete sense== | ||
The failure rate can be defined as the following: | |||
:The total number of failures within an item [[statistical population|population]], divided by the total time expended by that population, during a particular measurement interval under stated conditions. (MacDiarmid, ''et al.'') | |||
Although the failure rate, <math>\lambda (t)</math>, is often thought of as the [[probability]] that a failure occurs in a specified interval given no failure before time <math>t</math>, it is not actually a probability because it can exceed 1. Erroneous expression of the failure rate in % could result in incorrect perception of the measure, especially if it would be measured from repairable systems and multiple systems with non-constant failure rates or different operation times. It can be defined with the aid of the [[reliability function]], also called the survival function, <math>R(t)</math>, the probability of no failure before time <math>t</math>. | |||
== | ::<math>\lambda(t) = \frac{f(t)}{R(t)}</math>, where <math>f(t)</math> is the time to (first) failure distribution (i.e. the failure density function) and <math>R(t)=1-F(t)</math>. | ||
::<math>\lambda(t) = \frac{R(t_1)-R(t_2)}{(t_2-t_1) \cdot R(t_1)} | |||
= \frac{R(t)-R(t+\triangle t)}{\triangle t \cdot R(t)} \!</math> | |||
over a time interval <math>(t_2-t_1)</math> from <math>t_1</math> (or <math>t</math>) to <math>t_2</math> and <math>\Delta t</math> is defined as <math>(t_2-t_1)</math>. Note that this is a [[conditional probability]], hence the <math>R(t)</math> in the denominator. | |||
The <math>\lambda(t)</math> function is a CONDITIONAL probability of the failure DENSITY function. The condition is that the failure has not occurred at time <math>t</math>. | |||
Hazard rate and ROCOF (rate of occurrence of failures) are | |||
often incorrectly seen as the same and equal to the failure rate. And literature is even contaminated with inconsistent definitions. The hazard rate is in contrast to the ROCOF the same a failure rate. ROCOF is used for repairable systems only. In practice not many serious errors are made due to this confusion (although this statement is hard to validate...). | |||
==Failure rate in the continuous sense== | |||
[[Image:exponential distribution pdf.png|thumb|right|300px|Exponential failure density functions]] | |||
Calculating the failure rate for ever smaller intervals of time, results in the '''{{visible anchor|hazard function}}''' (also called '''hazard rate'''), <math>h(t)</math>. This becomes the ''instantaneous'' failure rate as <math>\scriptstyle\Delta t </math> tends to zero: | |||
:<math>h(t)=\lim_{\triangle t \to 0} \frac{R(t)-R(t+\triangle t)}{\triangle t \cdot R(t)}.</math> | |||
A continuous failure rate depends on the existence of a '''failure distribution''', <math>\scriptstyle F(t)</math>, which is a [[cumulative distribution function]] that describes the probability of failure (at least) up to and including time ''t'', | |||
:<math>\operatorname{Pr}(T\le t)=F(t)=1-R(t),\quad t\ge 0. \!</math> | |||
where <math>{T}</math> is the failure time. | |||
The failure distribution function is the integral of the failure [[probability density function|''density'' function]], ''f''(''t''), | |||
:<math>F(t)=\int_{0}^{t} f(\tau)\, d\tau. \!</math> | |||
The hazard function can be defined now as | |||
:<math>h(t)=\frac{f(t)}{1-F(t)}=\frac{f(t)}{R(t)}.</math> | |||
Many probability distributions can be used to model the failure distribution (''see [[List of probability distributions|List of important probability distributions]]''). A common model is the '''exponential failure distribution''', | |||
:<math>F(t)=\int_{0}^{t} \lambda e^{-\lambda \tau}\, d\tau = 1 - e^{-\lambda t}, \!</math> | |||
which is based on the [[exponential distribution|exponential density function]]. The hazard rate function for this is: | |||
:<math>h(t) = \frac{f(t)}{R(t)} = \frac{\lambda e^{-\lambda t}}{e^{-\lambda t}} = \lambda .</math> | |||
Thus, for an exponential failure distribution, the hazard rate is a constant with respect to time (that is, the distribution is "[[memorylessness|memory-less]]"). For other distributions, such as a [[Weibull distribution]] or a [[log-normal distribution]], the hazard function may not be constant with respect to time. For some such as the deterministic distribution{{citation needed|date=November 2010}} it is [[monotonic]] increasing (analogous to [[Wear and tear|"wearing out"]]), for others such as the [[Pareto distribution]] it is monotonic decreasing (analogous to [[Burn-in|"burning in"]]), while for many it is not monotonic. | |||
==Decreasing failure rate== | |||
A decreasing failure rate (DFR) describes a phenomenon where the probability of an event in a fixed time interval in the future decreases over time. A decreasing failure rate can describe a period of "infant mortality" where earlier failures are eliminated or corrected<ref>{{cite doi|10.1007/978-1-84800-986-8_1}}</ref> and corresponds to the situation where λ(''t'') is a [[decreasing function]]. | |||
Mixtures of DFR variables are DFR,<ref name="brown1980">{{cite doi|10.1214/aop/1176994773}}</ref> and also mixtures of [[exponential distribution|exponentially distributed]] random variables are DFR.<ref name="proschan" /> | |||
===Renewal processes=== | |||
For a [[renewal process]] with DFR renewal function, inter-renewal times are concave.<ref name="shanthikumar">{{cite doi|10.1214/aop/1176991910}}</ref><ref name="brown1980" /> Brown conjectured the converse, that DFR is also necessary for the inter-renewal times to be concave,<ref>{{cite doi|10.1214/aop/1176994317}}</ref> however it has been shown that this conjecture holds neither in the discrete case<ref name="shanthikumar" /> or continuous case.<ref>{{cite doi|10.1239/jap/1308662647}}</ref> | |||
===Applications=== | |||
Increasing failure rate is an intuitive concept caused by components wearing out. Decreasing failure rate describes a system which improves with age.<ref name="proschan" /> | |||
Decreasing failure rates have been found in the lifetimes of spacecraft, Baker and Baker commenting that "those spacecraft that last, last on and on."<ref>{{cite doi|10.2514/3.28040}}</ref><ref>{{cite doi|10.1002/9781119994077.ch1}}</ref> The reliability of aircraft air conditioning systems were individually found to have an [[exponential distribution]], and thus in the pooled population a DFR.<ref name="proschan">{{cite doi|10.1080/00401706.1963.10490105}}</ref> | |||
===Coefficient of variation=== | |||
When the failure rate is decreasing the [[coefficient of variation]] is ⩾ 1, and when the failure rate is increasing the coefficient of variation is ⩽ 1.<ref>{{cite doi|10.1016/S0167-6377(03)00061-0}}</ref> Note that this result only holds when the failure rate is defined for all t ⩾ 0<ref>{{cite book | title = Analysis of Queues: Methods and Applications | first = Natarajan | last =Gautam | publisher = CRC Press | year = 2012 | | page = 703 | isbn = 1439806586}}</ref> and that the converse result (coefficient of variation determining nature of failure rate) does not hold. | |||
==Failure rate data== | |||
Failure rate [[data]] can be obtained in several ways. The most common means are: | |||
;Historical data about the device or system under consideration: Many organizations maintain internal databases of failure information on the devices or systems that they produce, which can be used to calculate failure rates for those devices or systems. For new devices or systems, the historical data for similar devices or systems can serve as a useful estimate. | |||
;Government and commercial failure rate data: Handbooks of failure rate data for various components are available from government and commercial sources. [[#Online|MIL-HDBK-217F]], ''Reliability Prediction of Electronic Equipment'', is a [[military standard]] that provides failure rate data for many military electronic components. Several failure rate data sources are available commercially that focus on commercial components, including some non-electronic components. | |||
;Testing: The most accurate source of data is to test samples of the actual devices or systems in order to generate failure data. This is often prohibitively expensive or impractical, so that the previous data sources are often used instead. | |||
===Units=== | |||
Failure rates can be expressed using any measure of time, but '''hours''' is the most common unit in practice. Other units, such as miles, revolutions, etc., can also be used in place of "time" units. | |||
Failure rates are often expressed in [[engineering notation]] as failures per million, or 10<sup>−6</sup>, especially for individual components, since their failure rates are often very low. | |||
The '''Failures In Time''' ('''FIT''') rate of a device is the number of failures that can be expected in one [[1000000000 (number)|billion]] (10<sup>9</sup>) device-hours of operation. (E.g. 1000 devices for 1 million hours, or 1 million devices for 1000 hours each, or some other combination.) This term is used particularly by the [[semiconductor]] industry. | |||
The relationship of FIT to MTBF may be expressed as: MTBF = 1,000,000,000 x 1/FIT. | |||
===Additivity=== | |||
Under certain [[engineering]] assumptions (e.g. besides the above assumptions for a constant failure rate, the assumption that the considered system has no relevant [[Redundancy (engineering)|redundancies]]), the failure rate for a complex [[system]] is simply the sum of the individual failure rates of its components, as long as the units are consistent, e.g. failures per million hours. This permits testing of individual components or [[subsystem]]s, whose failure rates are then added to obtain the total system failure rate.{{Citation needed|date=November 2011}} | |||
===Example=== | |||
Suppose it is desired to estimate the failure rate of a certain component. A test can be performed to estimate its failure rate. Ten identical components are each tested until they either fail or reach 1000 hours, at which time the test is terminated for that component. (The level of statistical [[confidence interval|confidence]] is not considered in this example.) The results are as follows: | |||
Estimated failure rate is | |||
: <math>\frac{6\text{ failures}}{7502\text{ hours}} = 0.0007998 \frac{\text{failures}}{\text{hour}} = 799.8 \times 10^{-6} \frac{\text{failures}}{\text{hour}}, </math> | |||
or 799.8 failures for every million hours of operation. | |||
==Estimation== | |||
The [[Nelson–Aalen estimator]] can be used to estimate the cumulative hazard rate function. | |||
==See also== | |||
{{Portal|Statistics}} | |||
{{Div col|3}} | |||
*[[Annualized failure rate]] | |||
*[[Burn in]] | |||
*[[Failure mode]] | |||
*[[Force of mortality]] | |||
*[[Reliability engineering]] | |||
*[[Reliability theory]] | |||
*[[Reliability theory of aging and longevity]] | |||
*[[Survival analysis]] | |||
*[[Weibull distribution]] | |||
{{Div col end}} | |||
==References== | |||
{{Reflist}} | |||
*{{cite book |last=Blanchard |first=Benjamin S. |year=1992 |title=Logistics Engineering and Management |edition=Fourth |pages=26–32 |publisher=Prentice-Hall |location=Englewood Cliffs, New Jersey |isbn=0135241170 }} | |||
*{{cite book |last=Ebeling |first=Charles E. |year=1997 |title=An Introduction to Reliability and Maintainability Engineering |pages=23–32 |publisher=McGraw-Hill |location=Boston |isbn=0070188521 }} | |||
*[[Federal Standard 1037C]] | |||
*{{cite book |last=Kapur |first=K. C. |last2=Lamberson |first2=L. R. |year=1977 |title=Reliability in Engineering Design |pages=8–30 |publisher=John Wiley & Sons |location=New York |isbn=0471511919 }} | |||
*{{cite journal |last=Knowles |first=D. I. |year=1995 |title=Should We Move Away From ‘Acceptable Failure Rate’? |journal=Communications in Reliability Maintainability and Supportability |volume=2 |issue=1 |page=23 |publisher=International RMS Committee, USA }} | |||
*{{cite book |last=MacDiarmid |first=Preston |last2=Morris |first2=Seymour |last3=et al. |date=no date |title=Reliability Toolkit |edition=Commercial Practices |pages=35–39 |publisher=Reliability Analysis Center and Rome Laboratory |location=Rome, New York }} | |||
*{{cite book |last=Modarres |first=M. |last2=Kaminskiy |first2=M. |last3=Krivtsov |first3=V. |year=2010 |title=Reliability Engineering and Risk Analysis: A Practical Guide |edition=2nd |publisher=CRC Press |isbn=9780849392474 }} | |||
*{{cite journal |url=http://www.mitre.org/work/best_papers/02/mondro_approx/mondro_approx.pdf |last=Mondro |first=Mitchell J. |date=June 2002 |title=Approximation of Mean Time Between Failure When a System has Periodic Maintenance |journal=IEEE Transactions on Reliability |volume=51 |issue=2 |pages= |doi= }} | |||
*{{cite book |last=Rausand |first=M. |last2=Hoyland |first2=A. |year=2004 |title=System Reliability Theory; Models, Statistical methods, and Applications |publisher=John Wiley & Sons |location=New York |isbn=047147133X }} | |||
*{{cite book |last=Turner |first=T. |last2=Hockley |first2=C. |last3=Burdaky |first3=R. |year=1997 |title=The Customer Needs A Maintenance-Free Operating Period |work=1997 Avionics Conference and Exhibition, No. 97-0819, P. 2.2 |publisher=[[ERA Technology Ltd]]. |location=Leatherhead, Surrey, UK }} | |||
==External links== | |||
*[http://assist.daps.dla.mil/quicksearch/basic_profile.cfm?ident_number=53939 ''Reliability Prediction of Electronic Equipment'', MIL-HDBK-217F(2), (DOD download site.)] | |||
*[http://www.asq.org/reliability/articles/bathtub.html Bathtub curve issues by ASQC.] | |||
*[http://lamspeople.epfl.ch/kirrmann/Pubs/FT_Tutorial_HK_050418.pdf Fault Tolerant Computing in Industrial Automation by Hubert Kirrmann, ABB Research Center, Switzerland] | |||
*[http://www.faqs.org/faqs/arch-storage/part2/section-151.html Usenet FAQ about MTBF] | |||
*[http://www.eventhelix.com/RealtimeMantra/FaultHandling/reliability_availability_basics.htm Reliability and Availability Basics] | |||
*[http://www.weibull.com/hotwire/issue22/hottopics22.htm Product failure behavior and wear out] | |||
{{Statistics|analysis}} | |||
{{DEFAULTSORT:Failure Rate}} | |||
[[Category:Actuarial science]] | |||
[[Category:Statistical terminology]] | |||
[[Category:Failure]] | |||
[[Category:Reliability engineering]] | |||
[[Category:Survival analysis]] | |||
[[Category:Maintenance]] | |||
[[Category:Statistical ratios]] | |||
[[Category:Error measures]] | |||
[[ar:معدل الإخفاق]] | |||
[[de:Ausfallrate]] | |||
[[es:Función de riesgo]] | |||
[[fr:Taux de défaillance]] | |||
[[it:Tasso di guasto]] | |||
[[he:פונקציית סיכון]] | |||
[[ru:Интенсивность отказов]] | |||
[[simple:Failure rate]] | |||
[[sv:Felintensitet]] | |||
[[uk:Інтенсивність відмов]] | |||
Revision as of 00:30, 29 July 2013
Failure rate is the frequency with which an engineered system or component fails, expressed, for example, in failures per hour. It is often denoted by the Greek letter λ (lambda) and is important in reliability engineering.
The failure rate of a system usually depends on time, with the rate varying over the life cycle of the system. For example, an automobile's failure rate in its fifth year of service may be many times greater than its failure rate during its first year of service. One does not expect to replace an exhaust pipe, overhaul the brakes, or have major transmission problems in a new vehicle.
In practice, the mean time between failures (MTBF, 1/λ) is often reported instead of the failure rate. This is valid and useful if the failure rate may be assumed constant – often used for complex units / systems, electronics – and is a general agreement in some reliability standards (Military and Aerospace). It does in this case only relate to the flat region of the bathtub curve, also called the "useful life period". Because of this, it is incorrect to extrapolate MTBF to give an estimate of the service life time of a component, which will typically be much less than suggested by the MTBF due to the much higher failure rates in the "end-of-life wearout" part of the "bathtub curve".
The reason for the preferred use for MTBF numbers is that the use of large positive numbers (such as 2000 hours) is more intuitive and easier to remember than very small numbers (such as 0.0005 per hour).
The MTBF is an important system parameter in systems where failure rate needs to be managed, in particular for safety systems. The MTBF appears frequently in the engineering design requirements, and governs frequency of required system maintenance and inspections. In special processes called renewal processes, where the time to recover from failure can be neglected and the likelihood of failure remains constant with respect to time, the failure rate is simply the multiplicative inverse of the MTBF (1/λ).
A similar ratio used in the transport industries, especially in railways and trucking is "mean distance between failures", a variation which attempts to correlate actual loaded distances to similar reliability needs and practices.
Failure rates are important factors in the insurance, finance, commerce and regulatory industries and fundamental to the design of safe systems in a wide variety of applications.
Failure rate in the discrete sense
The failure rate can be defined as the following:
- The total number of failures within an item population, divided by the total time expended by that population, during a particular measurement interval under stated conditions. (MacDiarmid, et al.)
Although the failure rate, , is often thought of as the probability that a failure occurs in a specified interval given no failure before time , it is not actually a probability because it can exceed 1. Erroneous expression of the failure rate in % could result in incorrect perception of the measure, especially if it would be measured from repairable systems and multiple systems with non-constant failure rates or different operation times. It can be defined with the aid of the reliability function, also called the survival function, , the probability of no failure before time .
over a time interval from (or ) to and is defined as . Note that this is a conditional probability, hence the in the denominator.
The function is a CONDITIONAL probability of the failure DENSITY function. The condition is that the failure has not occurred at time .
Hazard rate and ROCOF (rate of occurrence of failures) are often incorrectly seen as the same and equal to the failure rate. And literature is even contaminated with inconsistent definitions. The hazard rate is in contrast to the ROCOF the same a failure rate. ROCOF is used for repairable systems only. In practice not many serious errors are made due to this confusion (although this statement is hard to validate...).
Failure rate in the continuous sense
Calculating the failure rate for ever smaller intervals of time, results in the Template:Visible anchor (also called hazard rate), . This becomes the instantaneous failure rate as tends to zero:
A continuous failure rate depends on the existence of a failure distribution, , which is a cumulative distribution function that describes the probability of failure (at least) up to and including time t,
where is the failure time. The failure distribution function is the integral of the failure density function, f(t),
The hazard function can be defined now as
Many probability distributions can be used to model the failure distribution (see List of important probability distributions). A common model is the exponential failure distribution,
which is based on the exponential density function. The hazard rate function for this is:
Thus, for an exponential failure distribution, the hazard rate is a constant with respect to time (that is, the distribution is "memory-less"). For other distributions, such as a Weibull distribution or a log-normal distribution, the hazard function may not be constant with respect to time. For some such as the deterministic distributionPotter or Ceramic Artist Truman Bedell from Rexton, has interests which include ceramics, best property developers in singapore developers in singapore and scrabble. Was especially enthused after visiting Alejandro de Humboldt National Park. it is monotonic increasing (analogous to "wearing out"), for others such as the Pareto distribution it is monotonic decreasing (analogous to "burning in"), while for many it is not monotonic.
Decreasing failure rate
A decreasing failure rate (DFR) describes a phenomenon where the probability of an event in a fixed time interval in the future decreases over time. A decreasing failure rate can describe a period of "infant mortality" where earlier failures are eliminated or corrected[1] and corresponds to the situation where λ(t) is a decreasing function.
Mixtures of DFR variables are DFR,[2] and also mixtures of exponentially distributed random variables are DFR.[3]
Renewal processes
For a renewal process with DFR renewal function, inter-renewal times are concave.[4][2] Brown conjectured the converse, that DFR is also necessary for the inter-renewal times to be concave,[5] however it has been shown that this conjecture holds neither in the discrete case[4] or continuous case.[6]
Applications
Increasing failure rate is an intuitive concept caused by components wearing out. Decreasing failure rate describes a system which improves with age.[3] Decreasing failure rates have been found in the lifetimes of spacecraft, Baker and Baker commenting that "those spacecraft that last, last on and on."[7][8] The reliability of aircraft air conditioning systems were individually found to have an exponential distribution, and thus in the pooled population a DFR.[3]
Coefficient of variation
When the failure rate is decreasing the coefficient of variation is ⩾ 1, and when the failure rate is increasing the coefficient of variation is ⩽ 1.[9] Note that this result only holds when the failure rate is defined for all t ⩾ 0[10] and that the converse result (coefficient of variation determining nature of failure rate) does not hold.
Failure rate data
Failure rate data can be obtained in several ways. The most common means are:
- Historical data about the device or system under consideration
- Many organizations maintain internal databases of failure information on the devices or systems that they produce, which can be used to calculate failure rates for those devices or systems. For new devices or systems, the historical data for similar devices or systems can serve as a useful estimate.
- Government and commercial failure rate data
- Handbooks of failure rate data for various components are available from government and commercial sources. MIL-HDBK-217F, Reliability Prediction of Electronic Equipment, is a military standard that provides failure rate data for many military electronic components. Several failure rate data sources are available commercially that focus on commercial components, including some non-electronic components.
- Testing
- The most accurate source of data is to test samples of the actual devices or systems in order to generate failure data. This is often prohibitively expensive or impractical, so that the previous data sources are often used instead.
Units
Failure rates can be expressed using any measure of time, but hours is the most common unit in practice. Other units, such as miles, revolutions, etc., can also be used in place of "time" units.
Failure rates are often expressed in engineering notation as failures per million, or 10−6, especially for individual components, since their failure rates are often very low.
The Failures In Time (FIT) rate of a device is the number of failures that can be expected in one billion (109) device-hours of operation. (E.g. 1000 devices for 1 million hours, or 1 million devices for 1000 hours each, or some other combination.) This term is used particularly by the semiconductor industry.
The relationship of FIT to MTBF may be expressed as: MTBF = 1,000,000,000 x 1/FIT.
Additivity
Under certain engineering assumptions (e.g. besides the above assumptions for a constant failure rate, the assumption that the considered system has no relevant redundancies), the failure rate for a complex system is simply the sum of the individual failure rates of its components, as long as the units are consistent, e.g. failures per million hours. This permits testing of individual components or subsystems, whose failure rates are then added to obtain the total system failure rate.Potter or Ceramic Artist Truman Bedell from Rexton, has interests which include ceramics, best property developers in singapore developers in singapore and scrabble. Was especially enthused after visiting Alejandro de Humboldt National Park.
Example
Suppose it is desired to estimate the failure rate of a certain component. A test can be performed to estimate its failure rate. Ten identical components are each tested until they either fail or reach 1000 hours, at which time the test is terminated for that component. (The level of statistical confidence is not considered in this example.) The results are as follows:
Estimated failure rate is
or 799.8 failures for every million hours of operation.
Estimation
The Nelson–Aalen estimator can be used to estimate the cumulative hazard rate function.
See also
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- Annualized failure rate
- Burn in
- Failure mode
- Force of mortality
- Reliability engineering
- Reliability theory
- Reliability theory of aging and longevity
- Survival analysis
- Weibull distribution
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References
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Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules
Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.
A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running
The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more
There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting
In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang
Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules
Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.
A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running
The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more
There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
External links
- Reliability Prediction of Electronic Equipment, MIL-HDBK-217F(2), (DOD download site.)
- Bathtub curve issues by ASQC.
- Fault Tolerant Computing in Industrial Automation by Hubert Kirrmann, ABB Research Center, Switzerland
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- ↑ 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534