Probability Of Failure-free Operation Research Articles

English

Software reliability is an important aspect of software quality. According to ANSI, it is defined as probability of failure-free operation of a computer program in a specified environment for a specified One of reliability's distinguishing characteristics is that it is objective, measurable, and can be estimated, whereas much of software quality is subjective criteria. This distinction is especially important in the discipline of SQA. These measured criteria are typically called software metrics. Although software reliability is defined as a probabilistic function, and comes with the notion of time, we must note that, software reliability is different from traditional hardware reliability, and not a direct function of time. Electronic and mechanical parts may become old and wear out with time and usage, but software will not rust or wear-out during its life cycle. Software will not change over time unless intentionally changed or upgraded. Neural Network-based Classification Method (NNCM) was used to classify the data using recordset cyclomatic density and design density. The records were preprocessed using normal distribution. The overall error in the classification using NNCM after normal distribution was found to be 0.38%. The reliability of classification with goodness of fit measure results in and forms the subsequent improvement of error classification among the dataset.

Reliability Analysis of Water Distribution Subsystem

Reliability Analysis of Water Distribution Subsystem This paper presents results of detailed reliability analysis of water distribution subsystem operation of Krakow city. Basis of the research was wide base of information of occurred failures during exploitation (1996-2006). These analysis included evaluation of basic factors such as: failure and renovation intensities, mean recovery time and mean time to failure, availability factor and probability of failure-free operation at any time. Moreover, it was performed wide analysis of failure capability of pipes as a function of its diameter and material. The paper consists also of research results of occurred piping failures reasons and consequences.

Using Software Reliability Growth Models in Practice

The amount of software in consumer electronics has grown from thousands to millions of lines of source code over the past decade. Up to a million of these products are manufactured each month for a successful mobile phone or television. Development organizations must meet two challenging requirements at the same time: be predictable to meet market windows and provide nearly fault-free software. Software reliability is the probability of failure-free operation for a specified period of time in a specified environment. The process of finding and removing faults to improve the software reliability can be described by a mathematical relationship called a software reliability growth model (SRGM). Our goal is to assess the practical application of SRGMs during integration and test and compare them with other estimation methods. We empirically validated SRGMs' usability in a software development environment. During final test phases for three embedded software projects, software reliability growth models predicted remaining faults in the software, supporting management's decisions.

Conditional Distributions of Ideal Reservoir Storage Variables

Storage capacity, yield, and reliability of a reservoir are random variables. Conditional distributions of these variables are studied by Monte Carlo simulation for operating periods up to 100 years. It is shown that these distributions are affected by the length of the period of operation due to the assumption of an initially full reservoir. Results of the study will aid in the reliability based reservoir design by clarifying the connection among the storage variables. The relationship between the steady-state reliability and the probability of failure-free operation over an N-year planning period is also investigated, and it is shown that the effect of the initial storage can be neglected only when the ratio of regulation is low.

Assessing the risk due to software faults: estimates of failure rate versus evidence of perfection

In the debate over the assessment of software reliability (or safety), as applied to critical software, two extreme positions can be discerned: the ‘statistical’ position, which requires that the claims of reliability be supported by statistical inference from realistic testing or operation, and the ‘perfectionist’ position, which requires convincing indications that the software is free from defects. These two positions naturally lead to requiring different kinds of supporting evidence, and actually to stating the dependability requirements in different ways, not allowing any direct comparison. There is often confusion about the relationship between statements about software failure rates and about software correctness, and about which evidence can support either kind of statement. This note clarifies the meaning of the two kinds of statement and how they relate to the probability of failure-free operation, and discusses their practical merits, especially for high required reliability or safety.

Relative information in the problem of controlling failure-free systems with data from components

We consider the problem of determining conformity of a system to stated requirements by using data from components with allowance for their freedom from failure. We obtain relations for determination of the sizes of autonomous tests and the lower confidence bound for the probability of failure-free operation.

Interaction between monitorability indicators and operational characteristics of communications equipment

This article considers the influence of changes in monitorability indicators on the operational characteristics of communications equipment. For indicators of monitorability we take the depth of defect search, failure localizability, overhead, and others. Among the operational characteristics, those considered include time to repair, probability of undetected failure, probability of failure-free operation, etc. The results obtained make it possible to estimate, during the design phase, the influence of changes in monitorability factors on the operational characteristics of equipment and to make selections that meet given requirements.

Analysis of effectiveness of compressor design stage in solving reliability problems

Calculation of compressor design reliability is based on structural reliability schemata (SRSs), employing two approaches: use of the reliability characteristics of actual compressor components or use of arbitrary design elements of the first and second types. As we know [i], from the standpoint of reliability a compressor constitutes a combination of arbitrary design elements of two types: those describing the working process in the compressor and those describing the status of compressor components and assemblies as a function of the action of mechanical and other factors that are not taken into account in describing the compressor working process (strength, strain, etc.). Arbitrary design elements of the first type include throughput, power consumed by the compressor, vibratory and acoustic characteristics, etc. Moreover, a compressor can be represented by a collection of real parametric and functional elements from the reliability standpoint [I]. A parametric element can have one or more basic operating characteristics that describe the working process in the element and one or more auxiliary working characteristics (strength, strain, wear, etc.) that describe the status of the element (assembly) and its components under the influence of mechanical and other factors. Thus, a parametric element is a combination of arbitrary design elements of both types in terms of reliability (as in the case of the compressor as a whole). Unlike a parametric functional element, a compressor can have just one or only a few main working characteristics, including strength, strain, wear, etc. A functional element is thus a combination of arbitrary design elements describing its basic working characteristics, which are series-connected in terms of reliability. Calculation of reliability from arbitrary design elements of the first and second types entails the use of a parametric model that takes into account the influence of gradual failures~ the influence of sudden failures must be allowed for by a separate component in the overall reliability estimate. We will consider the feasibility of applying these approaches to calculation of compressor reliability during different design stages. During the engineering proposal stage: the results of thermodynamic calculations for the compressor as a whole can be used to determine the probability of fault-free compressor operation with respect to throughput and power consumption (or, more precisely, its parametric component for gradual failures, i.e., a design element of the first type)~ here the draft contains none of the data needed for determination of the reliability component for the second type of design element (auxiliary working characteristics, i.e., strength, wear, etc.)~ sudden failures can be taken into account by utilizing data for an analogous compressor (which merely serves as a guideline, since the compressor under analysis has still not been fully worked out in terms of design) or the required failure-free operating parameters for the compressor being analyzed (rated failure-free operating time and mean time between failures)~ the estimate is also just a guideline in this case. At the working design stage: the refined data from the thermodynamic calculations can be used to obtain the sharpened parametric component of the initial probability of failure-free compressor operation from the main operating characteristics (throughput and power consumption); this constitutes an arbitrary design element of the first type in the compressor SRS; available design materials and the results yielded by computation of operating parameters for a number of important compressor assemblies and components can be employed to determine their parametric contribution to the probability of failure-free operation: it

Influence of design and other parameters on the rated reliability of helium compressors

The present article discusses the parametric component of reliability (based on gradual failures, but with account of the initial scattering of the characteristics), which can be calculated directly at the design stage of the compressor [i]. In this case reliability indicates failure-free performance, i.e., the ability of the object to retain a working condition continuously for a given time or to achieve production at given operating conditions without forced interruptions. Let us take the parametric component of the probability of failure-free operation of the compressor as the indicator of reliability.

Reliability analysis of ventilation systems

1. The reliabiity of devices switching the standby units by means of trapdoors in channels with unit-by-unit duplication is insufficient, because of the ineffective structure (series connections), difficult operational conditions, and impossibility by duplicating the components of the system. 2. The calculated probability of failure-free operation of an equivalent device for activating redundancy on systems with block-by-block duplication (scheme D), where the components are duplicated, and operational conditions are less demanding, is higher by 7.5 times than the reliability of the activating the redundancy unit with scheme A (VTsD fans); it is higher by a factor of 4.0 than the probability of failure-free operation of unit switching devices with scheme B (VOD fans). 3. The reliability of units with block-by-block redundancies (scheme D), where the units have separate backup duplication and the switching devices have a higher reliability, is greater by a factor of 2.4 than the reliability of systems based on scheme A (with VTsD fans), and by a factor of 1.5 than the scheme B (systems with VOD fans). 4. The reliability of systems based on schemes C and C′ is high, but their applications are limited by technological and engineering considerations, since the power of their drives is limited by the size of the fan sleeve, requiring a single-stage execution and low adaptability of the machine.

A method of finding the probability of failure-free operation of highly reliable systems

A method of finding the probability of failure-free operation of highly reliable systems

Discrepancies between readings of TPR-2075 thermoelectric thermometers

Thermoelectric devices with disposable sensing components (measuring heads~ are increasingly used in temperature monitoring during steel melting [1-3]. The probe is a steel tube of length several meters enclosing a two-wire conductor. One end of the tube has a handle together with a connector leading to the secondary instrument, while the other end of the tube is fitted with the disposable part of the device. This is constituted by a thermocouple having wires of diameter 0.08-0.12 mm, in which the hot junction is placed in a quartz tube and the cold junction is placed in a ceramic or plastic sleeve pressed or cemented into a paper outer sleeve. This sleeve protects the steel tube from failure and prevents the cold junction from becoming heated during the measurement, which usually takes only 7-15 sec. The design of the device, particularly the disposable section, is constantly being improved, especially with the object of improving the metrological characteristics, reliability, and cost. The Termopribor production organization in L'vov has designed the TPR-2075 platinumrhodium thermoelectric thermometer fitted with PTPR disposable tips, which are manufactured by the Teplopribor instrument-manufacturing plant in Chelyabinsk. These are designed for rapid (5 sec) measurement of the temperature of molten steel in convertors, steel-melting furnaces, and intermediate vessels in continuous-casting plants. The range covered is 13001800~ calibration for PR 30/6, probability of failure-free operation not less than 0.92. Figure 1 gives a general view of the TPR-2075, where 1 is the PTPR disposable tip, 2 is the mounting ring, 3 is the tube, 4 and 5 are respectively the body~ and handle, and 6 is the connector. The PTPR tip (Fig. 2) consists of the paper sleeve 2 of length I000 r~m, internal diameter 20 mm, and wall thickness 6.5 mm, which itself encloses the ceramic sleeve 3. The plastic insert 12 is cemented into the latter and bears the quartz U-tube 4 of outsidediameter 3 mm and wall thickness 0.8 mm. The tube is fitted with the elastic cover 9, which separates the refractory section 8 from the cold junctions 10 and II of the thermocouple 5, whose wires of diameter 0.1 mm are made of alloys PR 30 and PR 6. The design of the hot junction 6 ensures reliable thermal contact of the junction with the quartz tube and prevents failure due to the thermal shock on immersion in the metal [4]. Electrical contact between the thermocouple and the holder is provided by the extender leads 1 and 13, which are copper wires of diameter 1.0 mm (in the case of the PR 30 wire) or 0.8 mm (for the negative electrode). The metal cover 7 protects the quartz tube from mechanical damage on immersing the tip in the molten steel. As the PTPR tips are intended for use once only, the aspect of main interest from the metrological viewpoint is interchangeability. The main characteristic of the TPR-2075 is therefore the range in the readings, which characterizes [5] the performance of the means of measurement and reflects any deviation from zero in the average random error. The spread in the readings of the TPR-2075 has been examined for the range 1300-1700~ Random errors arise in temperature determination on account of the following deviations of the thermo-emf from the standard calibration (error ~,), the error o2 due to change in the temperature of the cold end during use, ~s due to inhomogeneity in the wire, ~ due to inhomogeneity in the copper wire, ss arising from temperature differences between the precious metal leads, and ~ the same arising from temperature differences between the copper parts of the circuit.