Accounting for maintenance in a computer memory reliability prediction model

This paper reviews the benefit of periodic maintenance for improving the reliability of computer memory protected by error detection and correction (EDAC), and presents a new memory reliability model that accounts for such maintenance. Mean time to failure (MTTF) has been the traditional figure of merit for assessing the benefit of memory maintenance. This paper proposes failure probability calculated at maintenance intervals as a more meaningful figure of merit for periodically maintained systems and presents examples using the new model.     

Availability and cost functions for periodically inspected preventively maintained units

Unavailability and cost rate functions are developed for components whose failures can occur randomly but they are detected only by periodic testing or inspections. If a failure occurs between consecutive inspections, the unit remains failed until the next inspection. Components are renewed by preventive maintenance periodically, or by repair or replacement after a failure, whichever occurs first (age-replacement). The model takes into account finite repair and maintenance durations as well as costs due to testing, repair, maintenance and lost production or accidents. For normally operating units the time-related penalty is loss of production. For standby safety equipment it is the expected cost of an accident that can happen when the component is down due to a dormant failure, repair or maintenance. The objective of maintenance optimization is to minimize the total cost rate by proper selection of two intervals, one for inspections and one for replacements. General conditions and techniques are developed for solving optimal test and maintenance intervals, with and without constraints on the production loss or accident rate. Insights are gained into how the optimal intervals depend on various cost parameters and reliability characteristics.     

Extended block diagram method for a multi-state system reliability assessment

The presented method extends the classical reliability block diagram method to a repairable multi-state system. It is very suitable for engineering applications since the procedure is well formalized and based on the natural decomposition of the entire multi-state system (the system is represented as a collection of its elements). Until now, the classical block diagram method did not provide the reliability assessment for the repairable multi-state system. The straightforward stochastic process methods are very difficult for engineering application in such cases due to the “dimension damnation”—huge number of system states. The suggested method is based on the combined random processes and the universal generating function technique and drastically reduces the number of states in the multi-state model.     

User control of electronic component reliability in spacecraft applications

This paper elucidates the role of the electronic component engineer in ensuring the reliability of electronic components for high reliability spacecraft applications. The reliability of electronic components is categorized in three areas of responsibility, attributable to the component manufacturer, the user and a shared responsibility between the two. The broad scope of the component engineer's responsibility extends from circuit design to system operation. Co-operation with circuit design engineers for proper part application is emphasized, and the requirements for understanding the effects of environmental stresses on device material properties is treated. The importance of a close working relationship between the component engineer and the part supplier is also emphasized.     

Maintenance free operating period – an alternative measure to MTBF and failure rate for specifying reliability?

The paper analyses the concept of maintenance free operating period (MFOP), the reliability requirement driven by the Ministry of Defence (UK) for the next generation of future aircraft to be included in the fleet. Since the traditional reliability requirement MTBF (mean operating time between failure) has several drawbacks, the immediate reaction would be to analyse the credibility of the new measure MFOP against MTBF. The paper discusses various issues associated with MFOP. Two mathematical models are developed to predict the maintenance free operating period survivability (MFOPS), one using mission reliability approach and the other using alternating renewal theory. The paper also analyses cost implications of MFOP to the customer and to the producer.     

Multi-state component criticality analysis for reliability improvement in multi-state systems

This paper evaluates and implements composite importance measures (CIM) for multi-state systems with multi-state components (MSMC). Importance measures are frequently used as a means to evaluate and rank the impact and criticality of individual components within a system yet they are less often used as a guide to prioritize system reliability improvements. For multi-state systems, previously developed measures sometimes are not appropriate and they do not meet all user needs. This study has two inter-related goals: first, to distinguish between two types of importance measures that can be used for evaluating the criticality of components in MSMC with respect to multi-state system reliability, and second, based on the CIM, to develop a component allocation heuristic to maximize system reliability improvements. The heuristic uses Monte-Carlo simulation together with the max-flow min-cut algorithm as a means to compute component CIM. These measures are then transformed into a cost-based composite metric that guides the allocation of redundant elements into the existing system. Experimental results for different system complexities show that these new CIM can effectively estimate the criticality of components with respect to multi-state system reliability. Similarly, these results show that the CIM-based heuristic can be used as a fast and effective technique to guide system reliability improvements.     

A model for preventive maintenance planning by genetic algorithms based in cost and reliability

This work has two important goals. The first one is to present a novel methodology for preventive maintenance policy evaluation based upon a cost-reliability model, which allows the use of flexible intervals between maintenance interventions. Such innovative features represents an advantage over the traditional methodologies as it allows a continuous fitting of the schedules in order to better deal with the components failure rates. The second goal is to automatically optimize the preventive maintenance policies, considering the proposed methodology for systems evaluation.Due to the great amount of parameters to be analyzed and their strong and non-linear interdependencies, the search for the optimum combination of these parameters is a very hard task when dealing with optimizations schedules. For these reasons, genetic algorithms (GA) may be an appropriate optimization technique to be used. The GA will search for the optimum maintenance policy considering several relevant features such as: (i) the probability of needing a repair (corrective maintenance), (ii) the cost of such repair, (iii) typical outage times, (iv) preventive maintenance costs, (v) the impact of the maintenance in the systems reliability as a whole, (vi) probability of imperfect maintenance, etc. In order to evaluate the proposed methodology, the High Pressure Injection System (HPIS) of a typical 4-loop PWR was used as a case study. The results obtained by this methodology outline its good performance, allowing specific analysis on the weighting factors of the objective function.     

New methods for specification and determination of component reliability characteristics

In the last two decades it has become clear that component lifetime distributions are seldom exponential. Early failures due to flaws have been of major concern. Various models to cater for this observation have been suggested. The models have been developed from a component rather from a system point of view. Furthermore, no substitute for the heavily criticized MIL-HDBK-217-type prediction handbooks has been offered. This paper describes a recently developed methodology to arrive at realistic component reliability characteristics, which take into account the non-exponential component lifetime distributions. These characteristics are developed from a system's point of view, which makes it easier for the system manufacturer to assess the reliability of their systems in the field. The methodology is based on six years of research in field performance of electronic systems. The research has been carried out in close co-operation with industrial companies.     

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.     

The efficient maintenance of offshore structural integrity using reliability analysis

Efficient maintenance of offshore structures is one of the priority development areas of the offshore industry world-wide. The maintenance of the installations in a hostile environment such as the North Sea poses a particular problem. Owing to the large number of wave-induced stress cycles experienced by the structures, the integrity is subject to progressive degradation under fatigue crack growth. If cracks are discovered in service, the operators of the structures will need to decide on the appropriate course of action. The priorities for actions will also need to be determined for cracks of various sizes found in different locations of the structures. In the past, the above decisions have depended very much on engineering judgement. However, the latest developments in reliability fracture mechanics (RFM) analysis have for the first time provided an objective criterion for this type of decision making. Moreover, this criterion is consistent with the established structural design criteria based on reliability analysis of strength—load interaction. Therefore, it has become a real possibility to incorporate structural integrity considerations by design. The reliability-fracture-mechanics-based fatigue analysis includes studies on the uncertainties of load history, materials crack growth behaviour, fracture mechanics modelling, non-destructive inspection and other environmental factors. This paper will review the development in this methodology. In order to integrate the above analysis into the overall design process, it is useful to carry out reliability analysis for the complete structural system. The current state of the art of structural system reliability analysis is therefore briefly reviewed. The necessary development in order to accommodate fatigue reliability degradation is then discussed.     

Methodology for the optimal component selection of electronic devices under reliability and cost constraints

The objective of this paper is to present an efficient computational methodology for the reliability optimization of electronic devices under cost constraints. The system modeling for calculating the reliability indices of the electronic devices is based on Bayesian networks using the fault tree approach, in order to overcome the limitations of the series–parallel topology of the reliability block diagrams. Furthermore, the Bayesian network modeling for the reliability analysis provides greater flexibility for representing multiple failure modes and dependent failure events, and simplifies fault diagnosis and reliability allocation. The optimal selection of components is obtained using the simulated annealing algorithm, which has proved to be highly efficient in complex optimization problems where gradient‐based methods can not be applied. The reliability modeling and optimization methodology was implemented into a computer program in Matlab using a Bayesian network toolbox. The methodology was applied for the optimal selection of components for an electrical switch of power installations under reliability and cost constraints. The full enumeration of the solution space was calculated in order to demonstrate the efficiency of the proposed optimization algorithm. The results obtained are excellent since a near optimum solution was found in a small fraction of the time needed for the complete enumeration (3%). All the optimum solutions found during consecutive runs of the optimization algorithm lay in the top 0.3% of the solutions that satisfy the reliability and cost constraints. Copyright © 2007 John Wiley & Sons, Ltd.     

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.     

Efficient surrogate models for reliability analysis of systems with multiple failure modes

Despite many advances in the field of computational reliability analysis, the efficient estimation of the reliability of a system with multiple failure modes remains a persistent challenge. Various sampling and analytical methods are available, but they typically require accepting a tradeoff between accuracy and computational efficiency. In this work, a surrogate-based approach is presented that simultaneously addresses the issues of accuracy, efficiency, and unimportant failure modes. The method is based on the creation of Gaussian process surrogate models that are required to be locally accurate only in the regions of the component limit states that contribute to system failure. This approach to constructing surrogate models is demonstrated to be both an efficient and accurate method for system-level reliability analysis.     

罗茨真空泵运行可靠性指标考核探讨

目前罗茨真空泵验收规范中采用零流量压缩比和最大允许压差来考核罗茨真空泵的性能。本文作者根据实际应用及可操作性,建议采用零流量压缩比和罗茨真空泵的排气口气体温度考核罗茨真空泵的性能。由于零流量压缩比的测量与现在的测量方法没有多大区别,因此本文没有详细讨论。     

Environmental testing and component reliability observations of telecommunications equipment operated in tropical climatic conditions

Safeguarding the reliability of electronics exposed to the severe conditions occurring in tropical climates, such as India, has not been adequately understood or dealt with in international specifications. Consequently, components and equipment supplied to such specifications have failed in such climates. The vulnerability of supposedly hermetic components has been suspected as a result of a full analysis of moisture ingress, and this has been borne out by comprehensive analyses of the actual failures of components supplied to international specifications, and the climatic conditions actually occurring in India. Understanding of reliability assessment and achievement has been significantly advanced by such analysis and has shown the necessity and applicability of the highly accelerated stress testing technique invented at British Telecom Laboratories more than two decades ago. Comparison has shown the significant cost benefit from the use of plastic encapsulated devices of proven reliability.     

Classification and calculation of primary failure modes in bread production line

In this study, we describe the classification methodology over a 2-year period of the primary failure modes in categories based on failure data of bread production line. We estimate the probabilities of these categories applying the chi-square goodness of fit test, and we calculate their joint probabilities of mass function at workstation and line level. Then, we present numerical examples in order to predict the causes and frequencies of breakdowns for workstations and for the entire bread production line that will occur in the future. The methodology is meant to guide bread and bakery product manufacturers, improving the operation of the production lines. It can also be a useful tool to maintenance engineers, who wish to analyze and improve the reliability and efficiency of the manufacturing systems.     

Reliability and cost optimization of electronic devices considering the component failure rate uncertainty

The objective of this paper is to present an efficient computational methodology to obtain the optimal system structure of electronic devices by using either a single or a multiobjective optimization approach, while considering the constraints on reliability and cost. The component failure rate uncertainty is taken under consideration and it is modeled with two alternative probability distribution functions. The Latin hypercube sampling method is used to simulate the probability distributions. An optimization approach was developed using the simulated annealing algorithm because of its flexibility to be applied in various system types with several constraints and its efficiency in computational time. This optimization approach can handle efficiently either the single or the multiobjective optimization modeling of the system design. The developed methodology was applied to a power electronic device and the results were compared with the results of the complete enumeration of the solution space. The stochastic nature of the best solutions for the single objective optimization modeling of the system design was sampled extensively and the robustness of the developed optimization approach was demonstrated.     

Short-term reliability of a brief hazard perception test

Hazard perception tests (HPTs) have been successfully implemented in some countries as a part of the driver licensing process and, while their validity has been evaluated, their short-term stability is unknown. This study examined the short-term reliability of a brief, dynamic version of the HPT. Fifty-five young adults (M_age = 21 yrs) with at least two years of post-licensing driving experience completed parallel, 21-scene HPTs with a one-month interval separating each test. Minimal practice effects (∼0.1 s) were manifested. Internal consistency (Cronbach's alpha) averaged 0.73 for the two forms. The correlation between the two tests was 0.55 (p < 0.001) and correcting for lack of reliability increased the correlation to 0.72. Thus, a brief form of the HPT demonstrates acceptable short-term reliability in drivers whose hazard perception should be stable, an important feature for implementation and consumer acceptance. One implication of these results is that valid HPT scores should predict future crash risk, a desirable property for user acceptance of such tests. However, short-term stability should be assessed over longer periods and in other driver groups, particularly novices and older adults, in whom inter-individual differences in the development of hazard perception skill may render HPT tests unstable, even over short intervals.     

The Bayes linear approach to inference and decision-making for a reliability programme

In reliability modelling it is conventional to build sophisticated models of the probabilistic behaviour of the component lifetimes in a system in order to deduce information about the probabilistic behaviour of the system lifetime. Decision modelling of the reliability programme requires a priori, therefore, an even more sophisticated set of models in order to capture the evidence the decision maker believes may be obtained from different types of data acquisition.Bayes linear analysis is a methodology that uses expectation rather than probability as the fundamental expression of uncertainty. By working only with expected values, a simpler level of modelling is needed as compared to full probability models.In this paper we shall consider the Bayes linear approach to the estimation of a mean time to failure MTTF of a component. The model built will take account of the variance in our estimate of the MTTF, based on a variety of sources of information.     

Error evaluations for the computation of failure probability in static structural reliability problems

The determination of mathematical reliability in static structures is still a motivating field of research. On one hand, the failure probability values are of greater importance in engineering activities; on the other hand, the determination of this probability remains a time consuming computational task when real problems are examined. To obtain a significant value for the failure probability while preserving a reasonable computation cost is therefore an objective to be considered. One of the necessary conditions to reach this target is to design a method to determine the computational error. Knowing the error will then give the capacity to limit the computation time, in particular by avoiding a too accurate probability evaluation. This paper presents a method allowing one to deal with these factors. The RGMR method, presented at the ICASP'7 meeting (July 1995, Paris) was designed to make such an error evaluation possible. Examples of numerical error computations with the RGMR method, particularly when low significant variables are eliminated, are given. These new developments are a step towards the goal mentioned above.