Device failure rates

In order to rninitnise the component count (and therefore the number of components that contribute to the device failure rate) there are a few constraints to the schematic design ... 

NOTE The evaluation of the SIF should take into account various factors, such as device failure rates and associated design, operation, maintenance, testing, inspection and management-of-change practices. 

The availability of the SIF is related to its ability to perform its design function when required. Improving availability means protecting the system against the consequences of random failures. Figures G.7 and G.8 illustrate how SIF performance can be maximized, and maintenance costs can be minimized. An In-Plant Reliability Data System (IPRDS) can provide data to serve as a basis for selecting device failure rates. This data can also provide a basis for the prior use evaluation of devices. (Refer to ISA-TR84.00.04-1 Annex L for more information on prior use.)... 

A concern regarding the probabiiistic approach used in iEC 61508 and ANSI/ISA-84.00.01-2004-1 to determine the adequacy of the SiF design is that owners/operators could mistakenly assume unrealistically low failure rates for the SIF devices. The resulting erroneously low PFDavg could potentially lead to inadequate risk reduction. There are many sources of failure rate data, and sometimes it is difficult to decide what number best represents the device in the field application. ISA-TR84.00.02 provides more information on device failure rates, including a sampling of data from five owners/operators. 

For field devices, extreme caution should be used in reducing the minimum fault tolerance from ANSI/ISA-84.00.01-2004-1, Clause 11.4.4, Table 6. Understanding the dangerous failure modes of the process interfaces is not trivial, and misapplication could result in the SIF being under-designed for the SIL target. Owners/operators should be cautious when using manufacturer data to support reduction in the fault tolerance and should review the assumptions, boundaries, and sources for the data. The methods used by manufacturers to calculate the device failure rate vary considerably. 

Other manufacturers use predictive models, involving estimated failure rates and assumed failure modes and distributions. While a mathematical model of the failure rate may appear more rigorous, a number of assumptions are made during the analysis that may or may not be valid for a particular field application. The assessment may not include the full device boundary (e.g., the process connection, the sensor, power supplies) or all components necessary to make a device functional. Further, the mathematical models often ignore the impact of the process on the device. When calculating the SFF, the device failure rate in the intended application is used. 

A second limitation relates to the boundary of coverage of failure modes covered by the lEC 61508 certification. The FMEA used to determine the device failure rates for an lEC 61508 SIL claim limit device is limited to the device boundary only and will typically not include potential dangerous failure modes of the process interfaces, installation parameters, power supplies, or communication interfaces. Failures associated with the process interfaces are very prominent in sensors, including plugged process lines, frozen lines, corrosion and gas permeation, and in valves, including seat damage, plugging, deposition, corrosion, and stem buildup. 

The analysis data, which can be interpreted by the reader for various apphcations, is in their report (RAC, 1991). Most vendors have reHabiUty reports on their products that discuss the results of accelerated life tests and provide a device failure rate. 

Device failure rates at different temperatures can be compared, using an extension of Equation 3.1. 

Although empirical relationships have been established relating certain device failure rates to specific stresses, such as voltage and temperature, no precise formula exists which links specific environments to failure rates. The permutation of different values of environmental factors is immense. General adjustment (multiplying) factors have been evolved and these are often used to scale up basic failure rates to particular environmental conditions. 

A considerable assumption in the exponential distribution is the assumption of a constant failure rate. Real devices demonstrate a failure rate curve more like that shown in Eigure 9. Eor a new device, the failure rate is initially high owing to manufacturing defects, material defects, etc. This period is called infant mortaUty. EoUowing this is a period of relatively constant failure rate. This is the period during which the exponential distribution is most apphcable. EinaHy, as the device ages, the failure rate eventually increases. 

Table 3 lists typical failure rate data for a variety of types of process equipment. Large variations between these numbers and specific equipment can be expected. However, this table demonstrates a very fundamental principle the more compHcated the device, the higher the failure rate. Thus switches and thermocouples have low failure rates gas—Hquid chromatographs have high failure rates. 

Figure 11 shows a system for controlling the water dow to a chemical reactor. The dow is measured by a differential pressure (DP) device. The controller decides on an appropriate control strategy and the control valve manipulates the dow of coolant. The procedure to determine the overall failure rate, the failure probabiUty, and the reUabiUty of the system, assuming a one-year operating period, is outlined hereia. 

The ha2ard function can be interpreted as the instantaneous failure rate. The quantity b(i)At for small A/ represents the probabiUty of failure in the interval At, given that the device was surviving at the beginning of the interval. 

The failure rate changes over the lifetime of a population of devices. An example of a failure-rate vs product-life curve is shown in Figure 9 where only three basic causes of failure are present. The quaUty-, stress-, and wearout-related failure rates sum to produce the overall failure rate over product life. The initial decreasing failure rate is termed infant mortaUty and is due to the early failure of substandard products. Latent material defects, poor assembly methods, and poor quaUty control can contribute to an initial high failure rate. A short period of in-plant product testing, termed bum-in, is used by manufacturers to eliminate these early failures from the consumer market. 

In some instances, plant-specific information relating to frequencies of subevents (e.g., a release from a relief device) can be compared against results derived from the quantitative fault tree analysis, starting with basic component failure rate data. 

In order to perform a complete, formal FMEA of a production facility, each failure mode of each device must be evaluated. A percentage failure rate and cost of failure for each mode for each device must be calculated. If the ri.sk discounted cost of failure is calculated to be acceptable, then there arc the proper numbers of redundancies. If that cost is not acceptable, then other redundancies must be added until an acceptable cost is attained. 

Determination of Reliability Characteristic Factors in the Nuclear Power Plant Biblis B, Gesellschaft fur Reaktorsicherheit mbH Nuclear Failure rates with upper and lower bounds and maintenance data for 17,000 components from 37 safety systems Data for pumps, valves, and electrical positioning devices, electric motors and drives from an operating power plant 66. 

This data collection effort was concentrated on the following components because of their extensive populations and repair action documentation pumps, valves, electrical positioning devices, electric motors, and drives. For each component type, preface pages and data summary tables are provided. Separate data summary tables are provided for each component type and are structured in a format that allows for the inclusion of the number of pieces of operating equipment, the total number of operating hours, total number of failures, and hourly failure rates with upper and lower bounds. 

Because prostheses are the most invasive treatment available, they are only considered in patients who do not respond to medications or external devices, or those who have significant adverse effects from other therapies. Patient satisfaction rates can be as high as 80% to 90% with partner satisfaction rates just slightly lower.9 The primary risks of insertion of prostheses are infection and device failure, although these only happen in 2% to 3% and 2% to 14% of patients, respectively. Higher infection rates have been reported in uncontrolled diabetic patients, paraplegics, and patients undergoing reimplantation or penile reconstruction.14,15 Most prostheses can be expected to last from 7 to 10 years.16... 

A number of other activation taggant techniques have been suggested, including the doping of explosives with material that would enhance the effectiveness of X-ray or similar devices. These concepts all lack specificity, however, and could cause the X-ray to be triggered by many common items, resulting in an unacceptable failure rate ... 

In other words, if a safety device is called on to act, there is a probability equal to ft that it will fail to do so. The importance of this simple formula is the demonstration that the probability of a safety device proving ineffective is directly linked to the failure rate of the device and the time interval between tests. 

It is very important to note that all this only applies to safety devices where the failure is hidden during normal plant operation. For, say, a normal control device where a failure would be immediately manifested by a malfunction of the plant, the hazard rate is simply the same as the failure rate. No amount of testing will help here. 

The failure rates and demand rates of safety devices are considered low. 

Power-traosistors that are commonly used in electronic devices consume large amount of electric power. The failure rate of electronic components increases almost exponentially with operating temperature, As a rule of thumb, the failure rate-lof electronic components is halved for each 10°C reduction in the junction operating temperature. Therefore, the operating temperature of electronic components is kept below a safe level to minimize the risk of failure. 

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