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17 USC 105 interim-entered record; under review. The article of record as published may be found at https://doi.org/10.1002/sys.21569 An open area of research for complex, cyber-physical systems is how to adequately support decision making using reliability and failure data early in the systems engineering process. Having meaningful reliability and failure data available early offers information to decision makers at a point in the design process where decisions have a high impact to cost ratio. When applied to conceptual system design, widely used methods such as probabilistic risk analysis (PRA) and failure modes effects and criticality analysis (FMECA) are limited by the availability of data and often rely on detailed representations of the system. Further, existing methods for system reliability and failure methods have not addressed failure propagation in conceptual system design prior to selecting candidate architectures. Consideration given to failure propagation primarily focuses on the basic representation where failures propagate forward. In order to address the shortcomings of existing reliability and failure methods, this paper presents the function failure propagation potential methodology (FFPPM) to formalize the types of failure propagation and quantify failure propagation potential for complex, cyber-physical systems during the conceptual stage of system design. Graph theory is leveraged to model and quantify the connectedness of the functional block diagram (FBD) to develop the metrics used in FFPPM. The FFPPM metrics include (i) the summation of the reachability matrix, (ii) the summation of the number of paths between nodes (i.e., functions) i and j for all i and j, and (iii) the degree and degree distribution. In plain English, these metrics quantify the reachability between functions in the graph, the number of paths between functions, and the connectedness of each node. The FFPPM metrics can then be used to make candidate architecture selection decisions and be used as early indicators for risk. The unique contribution of this research is to quantify failure propagation potential during conceptual system design of complex, cyber-physical systems prior to selecting candidate architectures. FFPPM has been demonstrated using the example of an emergency core cooling system (ECCS) system in a pressurized water reactor (PWR). Naval Postgraduate School (NPS) and United States Nuclear Regulatory Commission Naval Postgraduate School (NPS) and United States Nuclear Regulatory Commission Grant Number NRC-HQ- 84-14-G-0047

The goal of this research is to demonstrate the applicability of the Human Error and Functional Failure Reasoning (HEFFR) framework to complex engineered systems. Human errors are cited as a root cause of a majority of accidents and performance losses in complex engineered systems. However, a closer look would reveal that such mishaps are often caused by complex interactions between human fallibilities, component vulnerabilities, and poor design. Hence, there is a growing call for risk assessments to analyze human errors and component failures in combination. The HEFFR framework was developed to enable such combined risk assessments. Until now, this framework has only been applied to simple problems, and it is prone to be computationally heavy as complexity increases. In this research, we introduce a modular HEFFR assessment approach as means of managing the complexity and computational costs of the HEFFR simulations of complex engineered systems. Then, we validate the proposed approach by testing the consistency of the HEFFR results between modular and integral assessments and between different module partitioning assessments. Next, we perform a risk assessment of a train locomotive using the modular approach to demonstrate the applicability of the HEFFR framework to complex engineered systems. The results show that the proposed modular approach can produce consistent results while reducing complexity and computational costs. Also, the results from the train locomotive HEFFR analysis show that the modular assessments can be used to produce risk insights similar to integral assessments but with a modular context.

Risk-based design uses severity and occurrence quantification to determine overall system risk and prioritize the most important hazards. To fully understand and effectively mitigate potential risks, the effects of component failures and human errors (acting alone and in tandem) need to be considered early. Then one can determine whether to allocate resources to proactively mitigate human errors in the design process. In previous work, the Human Error and Functional Failure Reasoning (HEFFR) framework was developed to model effects of human errors and component failures in a system, taking critical event scenarios as inputs and producing functional failures, human errors, and their propagation paths as outputs. With automated scenario generation, this framework can model millions of scenarios that cause system critical functions to fail. However, the outputs of this framework do not include any quantifiable measures to assess the risk of the hazards or prioritize fault scenarios. This work addresses these shortcomings by using a scenario probability and cost model to quantify the expected cost of failures in the HEFFR framework. A coolant tank case study is used to demonstrate this approach. The results show that the quantifiable measures enable HEFFR to identify worst-case scenarios, prioritize scenarios with the highest impact, and improve human-product interactions. However, the underlying likelihood and cost models are subject to uncertainties which may affect the assessments.

The purpose of restoration strategy is to repair the combat system in time after the node is attacked so as to reduce the impact of functional failure. The combat system is modeled into a heterogeneous combat network, and its combat capability is measured by functional reliability based on the functional chain structure. This chapter proposes an edge increasing strategy with the goal of maximizing functional reliability and combines optional edges and connection costs as constraints. The artificial colony algorithm was used to solve the repair model. Simulation experiments were carried out under four node attack strategies. The results verify the effectiveness of the repair model and prove that the proposed method is superior to other repair algorithms.

This paper addresses the issue of PM scheduling for a complex mechanical with different failure modes. Unlike conventional studies which only consider a single failure mode without prior health information, our work jointly optimizes the failure time estimation and maintenance scheduling for mechanical systems under different failure modes. The proposed approach considers the failure modes which are fatal to the system function and performance. Firstly, the fatal failure modes are identified and divided into two types: the degraded and functional failure modes. The former indicates the one that has an explicit detectable degradation process till the predefined failure threshold is exceeded, while the latter indicates the failure modes that occur suddenly. For both types of failure modes, approaches of failure time estimation are presented to provide the actual health status information for maintenance scheduling. Afterwards, the maintenance scheduling problem is formulated on the estimated failure time distributions of the multiple failure modes. The integer-constrained genetic algorithm (GA) is adopted to optimize the preventive maintenance scheduling by minimizing the life-cycle cost rate. The optimal PM scheduling is derived based on the following: (1) when to perform the intermediate and major maintenance and (2) which failure mode should be maintained at an intermediate maintenance epoch. Finally, the performance of the proposed approach is validated through a real case of the ram subsystem of a boring machine.

In DEMO, the ex-vessel Remote Maintenance Systems (RMS) are responsible for the replacement and transportation of the plasma facing components. The ex-vessel operations of transportation (e.g. blankets or divertors) are performed by cranes or by means of trolleys. The blankets are extracted and transported vertically by cranes along galleries from the reactor to the storage or maintenance areas. An alternative is the transportation in horizontal configuration by means of trolleys along the galleries. A failure may occur in any situation, interrupting the current nominal operation. The work identifies a functional breakdown structure for the ex-vessel RMS operations and develops a Functional Failure Modes, Effects and Criticality Analysis (FFMECA). The results of the different FFMECA studies lead to the conclusions in terms of the most critical failure scenarios and the pros and cons of the horizontal versus the vertical transportation of blankets. In case of failure, a recovery procedure shall be triggered. The results will help the design process to improve and thus reduce the criticality index of the identified failures.

Human errors and poor ergonomics are attributed to a majority of large-scale accidents and malfunctions in complex engineered systems. Human Error and Functional Failure Reasoning (HEFFR) is a framework developed to assess potential functional failures, human errors, and their propagation paths during early design stages so that more reliable systems with improved performance and safety can be designed. In order to perform a comprehensive analysis using this framework, a wide array of potential failure scenarios need to be tested. Coming up with such use cases that can cover a majority of faults can be challenging or even impossible for a single engineer or a team of engineers. In the field of software engineering, automated test case generation techniques have been widely used for software testing. This research explores these methods to create a use case generation technique that covers both component-related and human-related fault scenarios. The proposed technique is a time based simulation that employs a modified Depth First Search (DFS) algorithm to simulate events as the event propagation is analyzed using HEFFR at each timestep. This approach is applied to a hold-up tank design problem and the results are analyzed to explore the capabilities and limitations.

As one of the most important means of nature gas peak shaving and energy strategic reserving, the reliability assessment of underground gas storage (UGS) system is necessary. Although many methods have been proposed for system reliability assessment, the functional heterogeneity of components and the influence of hydrothermal parameters on system reliability are neglected. To overcome these problems, we propose and apply a framework to assess UGS system reliability. Combining two-layer Monte Carlo simulation (MCS) technique with hydrothermal calculation, the framework integrates dynamic functional reliability of components into system reliability evaluation. To reflect the state transition process of repairable components and their impact on system reliability, the Markov model is introduced at system level. In order to improve the calculation speed, artificial neural network (ANN) model based on off-line MCS is established to replace the on-line MCS at components level. The proposed framework is applied to the reliability assessment and operation optimization of an UGS under different operation conditions. Compared with the traditional single-layer MCS method, the proposed method can not only reflect the variation of UGS reliability with hydrothermal parameters and operation time, but also can improve evaluation efficiency significantly.

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced functional failure identification and propagation (FFIP), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed toward the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. The capabilities of the proposed method is presented via a hold-up tank example, and the results are coupled with digital human modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.

Water pipes corrode as the endurance period elapses, or become deteriorated according to the buried environment, sometimes causing functional failure and problems with stable water supply. Stable and continuous water supply for consumers requires the risk assessment of water pipes. The safety factor has been used in many fields as a direct evaluation index that can express the state of a facility and is also used as a reference to judge the necessity of pipe renewal. In this study, the safety factor was calculated in order to establish the Probability of Failure model, by using result data such as the pipe property and ratio of residual stress from the technological inspection of waterworks.

An increased focus on risk based maintenance (RBM) optimization has been prompted in the offshore oil and gas (O&G) production and process industry due to the currently existing regulations and guidelines on preventing the functional failure risk (FFR) of rotating equipment and instrumentation. The RBM optimization approach prioritizes functions based on the potential risk of a given functional failure. Then, the equipment and instrumentation connected to the different functions are assigned with appropriate maintenance routines according to the potential risk of corresponding functional failure. This manuscript focuses on mitigating the suboptimal prioritizations made in implementing petroleum safety authority (PSA) specified regulations and NORSOK standard Z008 specified guidelines. It is mandatory to follow these to prevent functional failures on offshore O&G production and process facilities (P&PFs) operational on the Norwegian Continental Shelf (NCS). This manuscript suggests a fuzzy inference system (FIS) to minimize the suboptimal prioritizations of functions in the FFR analysis using an illustrative tailor-made risk matrix. This risk matrix has been developed to be similar to currently existing tailor-made risk matrices that have derived from Z008 guidelines and which have been used for FFR in different P&PF owner organizations operational on the NCS. Membership functions and the rule base were developed utilizing Z008 guidelines, data, experience, intuition and intentions of maintenance engineers. A risk rank calculation has been performed using the suggested FIS. The results indicate how the proposed approach helps in simplifying and making a more reliable and uniform FFR estimation.

The purpose of health prognostic is to predict the future health status of system and determine the time from the current health state to functional failure completely. Application data time series analysis method often can get the expected prediction effect. Taking into account the failure characteristics of the actuators in flight control system, the autoregressive moving average model is introduced to health prognostic. The prognostic model is established. The simulation results show the effectiveness of the algorithm.

While cyber–physical system sciences are developing methods for studying reliability that span domains such as mechanics, electronics and control, there remains a lack of methods for investigating the impact of the environment on the system. External conditions such as flooding, fire or toxic gas may damage equipment and failing to foresee such possibilities will result in invalid worst-case estimates of the safety and reliability of the system. Even if single component failures are anticipated, abnormal environmental conditions may result in common cause failures that cripple the system. This paper proposes a framework for modeling interactions between a cyber–physical system and its environment. The framework is limited to environments consisting of spaces with clear physical boundaries, such as power plants, buildings, mines and urban underground infrastructures. The purpose of the framework is to support simulation-based risk analysis of an initiating event such as an equipment failure or flooding. The functional failure identification and propagation (FFIP) framework is extended for this purpose, so that the simulation is able to detect component failures arising from abnormal environmental conditions and vice versa: Flooding could be caused by a failure in a pipe or valve component. As abnormal flow states propagate through the system and its environment, the goal of the simulation is to identify the system-wide cumulative effect of the initiating event and any related common cause failure scenario. FFIP determines this effect in terms of degradation or loss of the functionality of the system. The method is demonstrated with a nuclear reactor’s redundant coolant supply system.

In this paper, we introduce the overview of the requirements and the complementary information on the evaluation of containment functional failure frequency (CFF) in the revised version of “A Standard for Procedures of Probabilistic Risk Assessment of Nuclear Power Plants during Power Operation (Level 2 PRA) “[1] in Japan, which was developed and revised at the Level 2 PRA Subcommittee under the Atomic Energy Society of Japan (AESJ). Although the Level 2 PRA standard includes the evaluation of CFF and radiological source terms, we explain only the evaluation of CFF in this paper. In the evaluation of CFF, the physical response analysis and the probabilistic analysis are included as follows. The accident progression analysis is performed for each of the plant damage states, considering the operation status of mitigation systems, thermal-hydraulic behavior and core damage progression, and occurrences of some key events such as reactor pressure vessel failure. The containment event tree (CET) is developed classifying the accident progress in tree diagram. In the CET, some headings are arranged sequentially considering the accident progression. The headings correspond to the phenomena occurrence and the systems operation status, and a branch probability is assigned at each branch of heading. The branch probabilities of the phenomena are evaluated by either the Risk Oriented Accident Analysis Methodology (ROAAM) or the Decomposition Event Tree (DET) analysis considering the containment threats. The branch probabilities on the phenomena are set as the probability distributions, because the phenomena and the analysis have uncertainties. The branch probabilities on the systems operation are evaluated using the fault tree analysis and human error analysis. The containment functional failure modes are assigned at the end state of the CET considering the type of load against containment integrity. For the evaluation of the non-energetic load, the integral codes such as MELCOR [2], THALES-2 [3], and MAAP4 [4] etc. are used. On the other hand, various mechanistic codes are used for the evaluation of energetic phenomena such as steam explosion. The containment functional failure is judged by comparing the ultimate strength or the fragility of containment structure and the generated loads. After all, the CFF can be obtained by summing the frequency of containment functional failure mode. In the Level 2 PRA standard in Japan, the requirements in each evaluation process above are described. In addition, the technical background and the examples as the complementary information on each requirement are described in the Annex of the standard to help the application of the standard. In this revision, the body is revised to clarify the requirements on the quantification of the CET. The Annex is revised to incorporate the up-to-date information on severe accident research and severe accident management (SAM) measures. The updated information includes the melt stratification (OECD/MASCA project [5]), the steam explosion (SERENA project [6] and PULiMS/SES experiments [7]), the ex-vessel debris coolability (OECD/MCCI project [8]), debris jet breakup, the melt spreading, the coolability of the particulate bed, and the containment vessel (CV) fragility evaluation. Some future challenges are extracted from the lessons learned from the Fukushima Daiichi accident, such as development of the Level 2 PRA for the external hazard as earthquake and tsunami, quantification of impact on the containment integrity of hydrogen detonation in the adjacent buildings, and human error evaluation in the external hazard.

The functional deviations able to compromise system safety in the EU DEMO Primary Heat Transfer System (PHTS) with intermediate heat storage (IHS) based on molten salts are identified and compared to the deviations identified with PHTS without IHS. The resulting safety issues for the Balance of Plant (BoP) have been taken into account. Functional Failure Mode and Effects Analysis (FFMEA) is used to highlight the Postulated Initiating Events (PIE) of incident/accident sequences and to provide some safety insights during the preliminary design. The architecture of the system with IHS does not introduce new PIE with respect to the case without IHS, but it modifies some of them. In particular the two Postulated Initiating Events that are affected by the presence of IHS are the LOCA in the tubes of the HX between primary and intermediate circuit and the loss of heat sink for the first wall or the breeding zone. In fact the IHS introduces some advantages concerning the stability of the secondary circuit, but some weaknesses are associated to the physical-chemical nature of molten salts, especially oxidizing power, corrosive nature and risk of solidification. These issues can be managed in the design by the introduction of new safety functions.

No trouble found (NTF) due to functional failures is a common scenario today in board-level testing at system companies. A component on a board fails during the board-level functional test, but it passes the automatic test equipment (ATE) test when it is returned to the supplier for warranty replacement or service repair. To find the root cause of NTF, we propose an innovative functional test approach and discrete Fourier transform (DFT) methods for the detection of board-level functional failures. These DFT and test methods allow us to reproduce and detect functional failures in a controlled deterministic environment, and provide ATE tests to the supplier for early screening of defective parts. Experiments on an industry design show that the proposed functional scan test with appropriate functional constraints can adequately mimic the functional state space, as measured by appropriate coverage metrics. Experiments also show that most functional failures due to dominant bridging, crosstalk, and delay faults due to power supply noise can be reproduced and detected by functional scan test. We also describe two approaches to enhance the mimicking of the functional state space. The first approach allows us to select a given number of initial states in linear time and functional scan tests resulting from these selected states are used to mimic the functional state space. The second approach is based on controlled state injection.

For the purpose of determination of technical safety, and additional safety necessitated by public an social reasons, this paper considers methods of relations, probability and combined relation and probability. Also considered are functional failure and collapse failure, as well as the concept of designed service life of the structure. The ultimate safety degree is composed o the part for security regarding the technical and social consequences of collapse. The safety determination method, in technical terms too, strives to avoid the damage which would exceed the bearing capacity of the structure. The relation methods apply the safety degree which was obtained in cases when the similar structures of various dimensions were built, so it is necessary to determine the required dimensions to avoid the structural failure. The Probability method is widely applied using statistical data in the load and strength analysis. The combination of relation and probability methods provides the minimum safety degree as a reliable factor.

An item is subject to gradual degradation. The degradation can be represented by a measurable, non-negative and non-decreasing quantity. The item can be in one of three different states: normal (when the degradation quantity is smaller than a threshold of alarm or potential failure), functional failure (when the degradation quantity is larger than a functional failure threshold) and in-between or potential failure (when the degradation quantity is larger than the alarm threshold and smaller than the functional failure threshold). A sequential inspection scheme is implemented to determine the state of the item so as to prevent a functional failure. The paper presents a flexible degradation model and two cost models to optimize the alarm threshold and the sequential inspection scheme. The usefulness and appropriateness of the proposed models are illustrated by examples.

Passive systems are increasingly deployed in nuclear industry with an objective of increasing reliability and safety of operations with reduced cost. Methods for assessing the reliability of thermal–hydraulic passive systems, that is systems with moving working fluid, address the issues in natural buoyancy-driven flow that could result in a failure to meet the design safety limits under accident scenarios. This is referred as design functional reliability. This paper presents the results of functional reliability analysis carried out for the passive Safety Grade Decay Heat Removal System (SGDHRS) of Indian Prototype Fast Breeder Reactor (PFBR). The analysis is carried out based on the overall approach reported in the Reliability Methods for Passive System (RMPS, European Commission) project. Functional failure probability is calculated using Monte-Carlo method and also with method of moments.

This paper describes the debug and analysis process of a challenging case study from wafer foundry which involved a circular patch functional leakage failure that was induced from device parametric drift due to thicker gate oxide with no detection signal from inline monitoring vehicles. It highlights the need for failure analyst to always be inquisitive and to deep dive into the failure symptoms to value-add the fab in discovering the root cause of the failure in challenging situation where information is limited.

This paper presents a failure analysis of real industry case using FMECA method. The case study is conducted in a tyre manufacturing industry focusing on the machine components mechanism failures. Field failures record data are systematically analyzed to identify and classify the failure modes, effects and determined the criticality index on the subject under study. The details of step-by-step in applying FMECA according to the case study, the resultsand discussion have been presented accordingly. It is then concluded and proved that the FMECA method is beneficial to rank and prioritize failures systematically and thus help engineering team to perform the improvement project based on the right problem. Keywords : Failure analysis, Industry case study, Failure Mode Effect and Criticality Analysis (FMECA) 1. Introduction Every machine and process in daily manufacturing operations has it owns modes of failure. These modes of failures are where the state of termination of the ability of an item of any part, component, device, subsystem, functional unit, component or system that can be individually considered, to perform a required function takes in place as per definition by SS-EN 13306 [1]. In short, there are two types of failure which are the functional failure and the potential failure. A functional failure is the inability of an item or the component containing itto meet a specified performance standard meanwhile the potential failure is an identifiable physical condition which indicates a functional failure is imminent by referring to Nowlan and Heap [2].

In order to solve the problems of decision-making on inspection intervals of hidden functional failures for electronic equipment, a mathematical model was developed using probability and stochastic process theories. The maintenance costs were modeled by using the concept of delay time and considering the imperfect inspections. The optimal intervals of inspections were obtained by minimizing expected maintenance cost per unit time. And then, the corresponding optimization algorithm was presented, and an example was provided to show the optimization process and rectify the effectiveness of the algorithm.

As the technology keeps scaling down and IC design becomes more and more complex, failure analysis becomes much more challenging, especially for static fault isolation. For semiconductor foundry FA, it will become even more challenging due to lack of enough information. Static fault isolation is the major global fault isolation methodology in foundry FA and it is difficult to access and trigger the failing signal detected by scan and BIST test, which is widely applied in modern IC design. Because, in most of the time, the normal two pin bias (Vdd and Vss) can only get the comparable IV result between bad unit and the reference unit for function related fail. There are two possibilities from reverse engineering perspective. Firstly, the defect location may not be accessed by the DC bias. Secondly, even if the defect can be accessed, but the defect induced current or voltage change is too small to be differentiated from the overall signal. So it will be concealed in the overall current. However, it is still possible for us to do global fault isolation for the second situation. In this paper, a unit with Iddoff failure was analyzed. Although, no significant IV difference was observed between failed and reference units, a distinct Photon Emission (EMMI) spot was successfully observed in the failed unit. Layout analysis and process analysis on this EMMI spot further confirmed the reality of the emission spot.

Identifying aging effects that impact radiation hardness of microelectronics is becoming increasingly important as military weapon systems are kept in the stockpile for times beyond their originally intended use period. In this work, burn-in effects are used to demonstrate the potential impact of thermally-activated aging effects on integrated circuit radiation hardness. Static random access memories (SRAMs) from three different commercial technologies were irradiated with different pre-irradiation stress conditions. A reduction in the total dose functional failure level was observed for SRAMs from two of the technologies subjected to pre-irradiation elevated temperature stresses. This is the first time the burn-in effect has been shown to degrade the radiation-induced functional failure level of an IC. SRAM data also show no indication that the burn-in effect will saturate, at least for the conditions examined in this work. These data indicate that long-term aging can result in more device degradation than is accounted for by present hardness assurance test guidelines, potentially causing device and/or system failure during the aging period. While only a few technologies have been examined to date, we suspect other technologies may exhibit similar long-term aging effects. Technique for including aging effects within a hardness assurance test program is outlined.

Functional failures which were sensitive to temperature or voltage were usually seen in failure analysis and many strategies have been employed to solve this kind of failure. But some special failed ICs which were sensitive to light post decapsulation were difficult to handle. Three light sensitive functional failure cases were presented in this paper to show how we can find the root cause efficiently and what kind of mechanism lead to them sensitive to light.

In the weapon system, with the improvement of the equipment performance, the system complexity also increases. Functional failure will cause the system to malfunction or even become a disaster. Therefore, system-level comprehensive detection for Mission Electronic System is the urgent issue in the field of weaponry and equipment. First of all, this paper gives the definition of both static and dynamic problems, which are caused by the upgrade of the complexity. Secondly, we establish a formal model for static comprehensive detection, which include definitions of Mission Electronic System, system environment, consistency and adaption. Meanwhile, generic detection algorithm of consistency and suitability are put forward. Finally, we achieve the relevant system based in this model.

The problems that arise when analyzing functional failures and the fail-safety of aircraft equipment at the design and certification space of forms of functional failures of equipment and their models, the generation of incompatible forms of failures and their after-effects, and the calculation of the probabilities of their occurrence are also considered.

A degradation process is usually non-linear, and hence there exists one or more change points, where the degradation rate changes quickly. It is useful to determine the change points, e.g., designing an inspection scheme and predicting the time to a functional failure. It is an important issue how to specify the change points. This paper addresses this issue. A spline function with unknown knots is used to fit the observed degradation data and the estimated knots are the estimates of degradation change points. The information criterion is used to determine the optimal degree of spline function. The potential applications of the results are discussed, and the usefulness and appropriateness are illustrated by a real-world example.

This paper describes fragility evaluation results estimated by a seismic PRA procedure on the structural and functional failure of a building and equipment. The applicability of the response estimation method of the seismic PRA procedure is also discussed. The probability of failure is evaluated by a previously established PRA procedure and by Monte Carlo simulation. The response is calculated by five different methods in order to study the characteristics of simplified factors of the PRA procedure. According to the results, it is concluded that the proposed seismic PRA procedure gives adequate results when compared with the Monte Carlo simulation method. The PRA procedure can be used for a simplified evaluation method.

The high degree of flexibiliy required in FMS demands greater complexity in the system and consequently incurs a higher probability of a functional failure which necessitates some form of manual restoration. Unless appropriate measures are taken, frequent failures will not only interrupt the operations of the system, but also expose operating personnel to greater risks. Incorporating an appropriate contingency management capability in FMS will enable the system to automatically recover from a failure and continue operating. Greater attention is now given to improving the reliability of FMS using contingency management techniques. A majority of reported contingency strategies for FMS concern means for automatic recovery of robot-based systems. From a general review of known contingency strategies, four basic stages in the development of a contingency management system for FMS are identified and outlined. The framework for a contingency strategy employed in an assembly FMS is also introduced. The c...

In this paper, a comprehensive hierarchical-detection methodology for testability modeling is presented. At the beginning, interconnect test could be performed using boundary scan technology, then, general failure and functional failure could be detected and distinguished with multi-output of test indication, and lastly, two F-T matrix are built respectively, for F-failure and G-failure. By the examination and analysis, the modeling could lead the design for testability based on boundary scan and reduce fault ambiguities at a maximal degree.

Failure is a general term which can legitimately apply to an unsatisfactory output of an item from any cause, to an unsatisfactory output caused by an internal condition, to an unsatisfactory output caused by an input condition, to material in an item being in a damaged or broken condition, to a software failure condition, or to an unsatisfactory memory state. Distinctions among these types of failures should be made by preceding the word failure with an appropriate adjective - not by creating definitions for failure itself which are impractical and unnecessarily narrow.

Reliability Centered Maintenance (RCM) allows power companies to improve service quality and prevent equipment functional failure. This paper presents an RCM model for capacitor voltage transformers, which has been developed based on experience of maintenance crews of an important Brazilian power transmission company. Statistical assessment of failures in that company has been performed, in order to take into consideration a great number of failure possibilities. Some of these statistical data are presented along with relevant concepts and the major components of the developed RCM models.

The article is the Powerpoint presentation on specification of safety functions. The areas discussed include: hazard analysis; risk assessment; IEC 61508 requirements; functional failure analysis; failure modes; risk analysis; etc.

Specialized structures have been developed to understand how interconnect and via would link together in a circuit to bring out the weakest link in the interconnect-via system. This article reports a phenomenon where electromigration occurred in an actual circuit with signal lines connected by individual vias. A prediction is made into the weak link in the via-Interconnect system based on real time product. In the interconnect-via system used, the TiW barrier blocked the material flow from M2 to Ml. W plugs would block the material flow as they do with the barrier layers and the failures would occur at the via to interconnect interface as noticed in this case. Depending on the electron flow through the via, the material will either accumulate at the via-interconnect interface, which will induce inter-metal dielectric cracks, or deplete, causing discontinuity (opens) of the interconnect lines.

As process geometries shrink, leakage current is becoming an increasingly critical problem, especially in full-custom circuit designs. Excessive leakage may cause functional failure at some or all operating conditions. Traditional circuit analysis techniques may be used to verify if leakage currents are within allowable limits so as not to cause functional failures; however, unless the analysis takes into account specific input constraints for the circuit, the results may be overly pessimistic. We approach this noise analysis problem symbolically using algebraic decision diagrams (ADDs). Using ADDs allows us to efficiently analyze leakage within a channel-connected region (CCR) as a function of its inputs. Exclusivity constraints are easily included in the analysis, thus allowing for more accurate (and less pessimistic) results. Our approach is general and can be applied to any arbitrary circuit structure, including a mesh. The effectiveness of our approach is demonstrated on circuits from industry used in Alpha 21264 and 21364 instead of the usual ISCAS benchmarks. We show that such an analysis can lead to up to a 90% difference in worst case voltage drop. This difference can translate into significant savings in manpower by avoiding the need to verify many unrealizable worst-case conditions with other, more costly, simulation techniques.

Condition-based monitoring of power transformer insulation should center on the prediction of a substantial drop in the dielectric safety margin under the impact of moisture, oil by-products, contaminating particles, paper insulation aging and partial discharge activity. A functional failure model of power transformer insulation and possible effective methods of the insulation condition assessment are discussed based on practical experience.

For functional failure analysis, use of the scan design for effective testing of sequential circuits is very popular and can be considered the norm for the LSI industry. However, in order to take advantage of the features offered by scan designs, it is imperative that the scan chain is operating properly. In this paper, I will introduce a new technique for the efficient diagnosis of the scan chain. The basis for this paper is that if a failure occurs in the scan chain, irregular IDDQ current flow will occur and identify the defective chain. Moreover, the actual location of the failure inside the chain can also be ascertained. Then, with result of exemplification, I shall prove the effectiveness of this method.

RTCA DO-254, "Design Assurance Guidance for Airborne Electronic Hardware," outlines an approach for providing design assurance confidence for functions of a range of design assurance levels. In order to decompose the hardware functions, DO-254 provides a brief overview of Functional Failure Path Analysis (FFPA) but is limited in detail and provides no examples. This paper presents a detailed explanation of FFPA and illustrates it with a representative example.

Functional Hazard Assessment (FHA) is being increasingly recommended (e.g. by the Aerospace Recommended Practice-ARP 4754 [SAE94]) as a means of performing hazard identification. However, many of the available example applications of this approach (including that given in ARP 4761 [SAE95]) are illustrated either for aircraft-level functions or sub-system functions with obvious and visible functional effects. Our experience is that it can be difficult to apply FHA for lower level aircraft systems (specifically at the level of the engine controller) where, due to the level of complexity and integration with other systems, the overall effects of functional failure are far from obvious. In this paper, we describe the problems we have encountered when applying FHA and the (partial) solutions we have proposed in order to overcome these problems. (6 pages)

The current paper presents the application of three maintenance techniques, namely, age replacement-based maintenance (ARBM), wear rate-based maintenance (WRBM), and output-based maintenance (OBM), for replacement decision making. The first two techniques are available in the literature, whereas the third one is a technique proposed in the present paper. The theory and principles underlying each technique are briefly discussed before the applicability of each is validated through a case study in the pulp manufacturing industry. The results of each maintenance technique for replacement decision making are compared and discussed from a practical point of view. The present paper concludes that OBM, the proposed technique, provides a more realistic approach towards replacement decision making compared with the other two techniques for functional failure type component. This conclusion is supported by a review of the entire process of replacement decision making based on four practicability criteria, namely, the basic theory and principle of each technique, data requirements and challenge in data collection, data analysis/modelling, and the decision process. Future research recommendations for the application of OBM are also given.

General relationships between individual joint reliability and overall system reliability in a redundant structure with no repair program are presented. Using a fatigue reliability model, a Monte Carlo analysis provided a distribution of time to failure for various degrees of redundancy. Random variables in the model account for uncertainty in the process of determining fatigue strengths of the joints. The distribution parameters for these random variables are representative of welded tubular joints in offshore platforms. Figures are shown which relate the target safety index of a joint to the reliability against various definitions of “functional failure” of the structure. Also included is an example of how the probability of a second failure occurring within a specified time interval after an initial failure can be predicted. This can provide insight in determining the necessary frequency of inspections.

The abrupt failure of devices under test - especially during step-stress measurements presents special problems in determining parameter end points. This article shows how past procedures can be replaced by a method which can be applied with equal logical consistency to both the graceful degradation of parts as well as to the abrupt failure of parts. The article gives an example of how the method works and discusses its advantages and disadvantages

RTCA DO-254, “Design Assurance Guidance for Airborne Electronic Hardware,” the best industry practice and experience for the airborne hardware design assurance, outlines an approach for providing design assurance confidence for functions of a range of design assurance levels. DO-254 using functional failure path analysis (FFPA) method to decompose the hardware functions, verify it so as to achieve the purpose of compliance with safety requirements. However, is limited in detail and providers no examples, making it difficult to understand for engineering designer based on the development and application. This article will research the function failure path analysis (FFPA) method, and illustrates it with an aeronautical engineering case by LRU example to enhance understanding and to accumulate experience of applications for DO-254.

The 8086 microprocessor has been characterized for total dose response. Commercial and military-standard devices implemented in HMOS II technology as well as commercial devices implemented in HMOS technology were tested. Functional failures were observed between 6.8 krad(Si) and 25.9 krad(Si). The effect of fabrication technology and of variation in clock frequency is discussed. Functional failure modes as determined by test software are listed.

This test procedure defines the detailed requirements for gamma dose rate testing of semiconductor integrated circuits to determine if they are susceptible to radiation-induced latchup. This test is not deleterious, and devices which have been subjected to and passed the test may be used as production hardware. There are two types of radiation-induced latchup: (1) a hard latchup, and (2) an incipient latchup. A hard latchup is a sustained functional failure. The erroneous operational condition can be stopped by cycling bias power if burnout has not occurred in the interim. Incipient latchup is characterized by a functional failure which is not sustained, but which lasts longer than can be explained by normal circuit time constants. Identification of a latchup-susceptible IC is accomplished by identifying erroneous operating states immediately after radiation exposure by exercising the device with a functional test.