The reliability physics approach to failure prediction modelling

Empirically based failure rate modelling methodologies employed in reliability prediction handbooks, and deterministic modelling methods are both critically examined using microelectronic packages as vehicles. As an alternative, a coupled mechano-stochastic approach to reliability prediction modelling is presented. The goal is to use physics of failure principles with appropriate failure probability density distributions to design for failure-free operation and predict failure times for components now available, as well as new components resulting from new materials, technologies and processes. In addition, an approach for extending the model to aid in logistics support analysis is discussed.     

Reliability prediction: A constructive critique of MIL-HDBK-217E

MIL-HDBK-217E is based on some major fallacies and oversimplifications. These include the assumption of constant failure rate, the assumed independence of the Pi factors, the oversimplification of temperature dependence, the neglect of process yield and screening fall-out as determinants in the categorization of quality grade and the absence of manufacturing date information. These weaknesses are discussed and some recommendations made.     

Application of modern reliability database techniques to military system data

This paper focuses on analysis techniques of modern reliability databases, with an application to military system data. The analysis of military system data base consists of the following steps: clean the data and perform operation on it in order to obtain good estimators; present simple plots of data; analyze the data with statistical and probabilistic methods. Each step is dealt with separately and the main results are presented.Competing risks theory is advocated as the mathematical support for the analysis. The general framework of competing risks theory is presented together with simple independent and dependent competing risks models available in literature. These models are used to identify the reliability and maintenance indicators required by the operating personnel. Model selection is based on graphical interpretation of plotted data.     

A reliability centered approach to remote condition monitoring. A railway points case study

Railway turnouts, consisting of switches and a crossing, are complex electro-mechanical devices which are exposed to severe environmental influences and which are essential for the operation of any railway bar horizontal lifts. Their safe and reliable operation must be assured if the rail mode of transport is to flourish. Conventionally, the continuous availability of turnout mechanisms has been assured by high levels of routine maintenance, to some extent tailored to the criticality of a particular point location. However, traffic increases and shortened maintenance windows require better approaches to turnout maintenance. The authors of the present paper undertook the development of algorithms to detect gradual failure in railway turnout which should allow a move to an RCM² approach to the management of switch and crossing maintenance. They demonstrate the approach using data from tests on a commonly found point mechanism and include a discussion of the benefits of adopting a Kalman Filter for pre-processing the data collected during tests.     

Microelectronic reliability/temperature independence

It is shown that microelectronic failures which occur within equipment operating temperature extremes are not dependent on absolute temperature! Therefore, tremendous equipment reductions can be made in size, weight and cost, and there will be an improvement in reliability by elimination of failures due to unreliable complex cooling systems.     

The rationale of reliability prediction

This paper is the first of what is intended to be a series of papers which investigate the foundations of reliability theory, particularly when applied to the prediction process. It will contrast current reliability practice against those practices common in normal science and engineering. The claim will be made that in general the prediction process as used in reliability, when stripped of the mathematical embellishments, is no more than simple enumeration: a method long held by the philosophers of science to be unreliable and in general a poor basis on which to make predictions. This initial paper rejects the statistical method as being an insufficient basis for making predictions and claims that it is incapable of logically supporting its conclusions. Although no evidence is provided to substantiate this claim, a number of scientific methods, both of historical and present day importance, are briefly reviewed with which one can contrast the statistical method.     

A fuzzy logic based approach to reliability improvement estimation during product development

During early stages of product development process, a vast amount of knowledge and information is generated. However, most of it is subjective (imprecise) in nature and remains unutilized. This paper presents a formal structure for capturing this information and knowledge and utilizing it in reliability improvement estimation. The information is extracted as improvement indices from various design tools, experiments, and design review records and treated as fuzzy numbers or linguistic variables. Fuzzy reasoning method is used to combine and quantify the subjective information to map their impact on product reliability. The crisp output of the fuzzy reasoning process is treated as new evidence and incorporated into a Bayesian framework to update the reliability estimates. A case example is presented to demonstrate the proposed approach.     

A reduced sampling approach for reliability verification

Reliability demonstration tests frequently require large sample sizes which are objectionable from both a cost and time standpoint. The approach presented, referred to as bias sampling, offers a means to demonstrate conformance to reliability objectives with reduced test samples and test time. The reduction is achieved by selection and test of samples from the lower-median sub-population of a random sample. The prediction assumes that the entire population of samples was tested. Rationale for the approach is presented along with guidelines for sample selection. Two application examples illustrate how the methodology is being employed at Chrysler Corporation.     

Optoelectronics reliability

This paper reviews degradation modes and reliability in several kinds of InGaAsP/InP lasers and photodetectors used in optical fibre transmission systems. From the viewpoint of degradation mechanisms, BH type Fabry–Perot lasers, DFB lasers, a 0.98 μm strained quantum well InGaAs/GaAs laser, and InGaAs PIN photodetectors and APDs are reviewed.     

Regression approach to tire reliability analysis

The paper considers an empirical approach to the root-cause analysis of a certain kind of automobile tire failure. Tire life data are obtained from a laboratory test, which is developed to duplicate field failures. A number of parameters related to tire geometry and physical properties are selected as explanatory variables that potentially affect a tire's life on test. Analysis of the life test data is performed via the Cox survival regression model. The paper also elaborates on the application of an ordinary (non-survival) linear regression to modeling the failure initiation and propagation. The developed statistical models help to identify the elements of tire design affecting the probability of tire failure due to the failure mode in question.     

A convenient approach for estimating time-dependent structural reliability in the load space

A procedure, formulated in the space of the load processes, is described for estimating the reliability of structures subject to multi-parameter time-varying loading. For most realistic reliability problems the load process space is of low order. As a result, the required multidimensional integration is significantly simplified. The proposed approach also has well defined steps. As a result, there is increased transparency and reduced problems of integration instability and non-convergence. Both loads and resistances are described in terms of random variable parameters and time dependent structural resistances can be considered. Numerical examples are given to illustrate the proposed method. Example applications are given for a fixed base rigid-plastic portal frame subjected to time dependent loads and resistances. Linear and non-linear limit state equations and Normal and non-Normal distribution of the random variables are considered and compared, in some cases, to the results evaluated using Monte Carlo simulation.     

What is wrong with the existing reliability prediction methods?

Inaccurate reliability predictions could lead to disasters such as in the case of the U.S. Space Shuttle failure. The question is: ‘what is wrong with the existing reliability prediction methods?’ This paper examines the methods for predicting reliability of electronics. Based on information in the literature the measured vs predicted reliability could be as far apart as five to twenty times. Reliability calculated using the five most commonly used handbooks showed that there could be a 100 times variation. The root cause for the prediction inaccuracy is that many of the first-order effect factors are not explicitly included in the prediction methods. These factors include thermal cycling, temperature change rate, mechanical shock, vibration, power on/off, supplier quality difference, reliability improvement with respect to calendar years and ageing. As indicated in the data provided in this paper any one of these factors neglected could cause a variation in the predicted reliability by several times. The reliability vs ageing-hour curve showed that there was a 10 times change in reliability from 1000 ageing-hours to 10,000 ageing-hours. Therefore, in order to increase the accuracy of reliability prediction the factors must be incorporated into the prediction methods.     

Increasing importance of effects of marginal parts on reliability

In this paper, marginal parts are equated with low quality and low reliability. Marginal parts can be shown to cause errors in some products during tests. They are also a cause of field failures in these products. Although marginal parts causes still have a random failure time component, they have a much lower amount of variation than our traditional failure causes, hidden flaws. I give marginal parts a measurable definition. If marginal effects can be established for a product, then this knowledge can be used to improve reliability. Some examples of products where I believe this marginal effect holds are discussed in this paper. Such marginal effects on reliability are gaining more and more importance in systems that are increasing in complexity. A strong point in applying the marginal parts theory framed in this paper is that it can be readily subjected to statistical testing to see if it holds or not for any particular product.     

The classification and regression tree approach to pump failure rate analysis

In this article, a technique based on rule induction is suggested as non-parametric alternative to determine the expected failure rates of 143 centrifugal pumps included in a oil refinery plant and subjected to different operating conditions. At the same time, the procedure makes it possible to determine the critical operating factors influencing the reliability of the pumps. In particular, the classification and regression tree approach is used to automatically generate rules from an extended data base of the plant concerning information about failures and operating conditions of the different facilities.     

A rule induction approach to improve Monte Carlo system reliability assessment

A Decision Tree (DT) approach to build empirical models for use in Monte Carlo reliability evaluation is presented. The main idea is to develop an estimation algorithm, by training a model on a restricted data set, and replacing the Evaluation Function (EF) by a simpler calculation, which provides reasonably accurate model outputs. The proposed approach is illustrated with two systems of different size, represented by their equivalent networks. The robustness of the DT approach as an approximated method to replace the EF is also analysed. Excellent system reliability results are obtained by training a DT with a small amount of information.     

Maintenance, reliability and policies for orbital space station life support systems

The performance of productive work on space missions is critical to sustaining a human presence on orbital space stations (OSS), the Moon, or Mars. Available time for productive work has potentially been impacted on past OSS missions by underestimating the crew time needed to maintain systems, such as the Environmental Control and Life Support System (ECLSS). To determine the cause of this apparent disconnect between the design and operation of an OSS, documented crew time for maintenance was collected from the three Skylab missions and Increments 4–8 on the International Space Station (ISS), and the data was contrasted to terrestrial facility maintenance norms. The results of the ISS analysis showed that for four operational and seven functional categories, the largest deviation of 60.4% over the design time was caused by three of the four operational categories not being quantitatively included in the design documents. In a cross category analysis, 35.3% of the crew time was found to have been used to repair air and waste handling systems. The air system required additional crew time for maintenance due to a greater than expected failure rate and resultant increased time needed for repairs. Therefore, it appears that the disconnect between the design time and actual operations for ECLSS maintenance on ISS was caused by excluding non-repair activities from the estimates and experiencing greater than expected technology maintenance requirements. Based on these ISS and Skylab analyses, future OSS designs (and possibly lunar and Martian missions as well) should consider 3.0–3.3 h/day for crews of 2 to 3 as a baseline of crew time needed for ECLSS maintenance.     

A method for analysing the reliability of a transmission grid

The paper describes a probabilistic method for transmission grid security evaluation. Power system security is the ability of the power system to withstand sudden disturbances such as short circuits. The method presented here uses event and fault trees and combines them with power system dynamic simulations. Event trees model the substation protection and trip operations after line faults. Different event tree end states (fault duration, circuit breaker trips) are simulated with power system dynamic analysis program. The dynamic analysis results (power system post-fault states) are then classified into secure, alert, emergency and system breakdown. The probabilities, minimal cut sets and grid level importance measures (Fussell-Vesely, risk increase and decrease factors) are calculated for the total and partial system breakdown. In this way, the relative importance of the substation devices regarding to the system breakdown can be reached. Also the more and less likely contributing factors to system breakdown are received. With this method, an existing 400 kV transmission grid with its line fault and device failure statistics is analysed.     

A new approach to the d-MC problem

Many real-world systems (such as cellular telephones, transportation, etc.) are multistate-node acyclic network (MNAN) composed of multistate-nodes. Such network has a source node (position) where the signal source is located, a number of sink nodes that only receive the signal, and a number of intermediate nodes that retransmit the received signal to some other nodes. The non-sink node has different states determined by a set of nodes receiving the signal directly from it. The reliability of MNAN can be computed in terms of minimal trees (MTs). Based on the Branch-and-Bound algorithm, we developed an intuitive algorithm that is simpler than the best-known existing method. The computational complexity of the proposed algorithm is also analyzed. One example is illustrated to show how all MTs are generated by the proposed algorithm. The reliability of this example is then computed.