Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925797
J.B. Farmer, P. Ellner
Reliability is the probability that a system will perform its intended function for a specified period of time in a specified environment. Often, the reliability of a system cannot be directly measured through test to compare against its requirement because of programmatic constraints on testing. In cases where testing cannot adhere exactly to the defined mission profile, it is necessary to normalize the resulting test data to evaluate reliability performance against the system requirement. This paper describes the application of normalization techniques to reliability test data on the marine corps expeditionary fighting vehicle (EFV) program.
{"title":"System reliability evaluation using normalized test data","authors":"J.B. Farmer, P. Ellner","doi":"10.1109/RAMS.2008.4925797","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925797","url":null,"abstract":"Reliability is the probability that a system will perform its intended function for a specified period of time in a specified environment. Often, the reliability of a system cannot be directly measured through test to compare against its requirement because of programmatic constraints on testing. In cases where testing cannot adhere exactly to the defined mission profile, it is necessary to normalize the resulting test data to evaluate reliability performance against the system requirement. This paper describes the application of normalization techniques to reliability test data on the marine corps expeditionary fighting vehicle (EFV) program.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"28 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121333353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925827
N. Ozarin
Bent pin analysis is an important kind of failure modes and effects analysis that almost always ignores real-world behavior. The somewhat undisciplined nature of this FMEA means there is heavy reliance on human judgment, and given the particularly tedious nature of the task, the results are typically both incomplete and inaccurate. The analysis also provides oversimplified predictions of failure rates based on averages, or omits them entirely. However, carefully defining analysis rules that more realistically reflect real-world events make it possible for a computer to perform a great deal of the task with far more accuracy. Using these rules, the computer can determine individual failure rates for each permutation of short and open circuits. The computer can also go beyond these computations and do a great deal of additional analysis work, freeing humans to concentrate on circuits and systems instead of pins and wires. Finally, the computer can automatically supply repeated worksheet information - and bent pin FMEA worksheets have a lot of it - so that you never need to enter anything more than once. The result is a far more accurate, consistent, and complete analysis requiring much less effort. It brings bent pin analysis into the 21st century.
{"title":"What's wrong with bent pin analysis, and what to do about it","authors":"N. Ozarin","doi":"10.1109/RAMS.2008.4925827","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925827","url":null,"abstract":"Bent pin analysis is an important kind of failure modes and effects analysis that almost always ignores real-world behavior. The somewhat undisciplined nature of this FMEA means there is heavy reliance on human judgment, and given the particularly tedious nature of the task, the results are typically both incomplete and inaccurate. The analysis also provides oversimplified predictions of failure rates based on averages, or omits them entirely. However, carefully defining analysis rules that more realistically reflect real-world events make it possible for a computer to perform a great deal of the task with far more accuracy. Using these rules, the computer can determine individual failure rates for each permutation of short and open circuits. The computer can also go beyond these computations and do a great deal of additional analysis work, freeing humans to concentrate on circuits and systems instead of pins and wires. Finally, the computer can automatically supply repeated worksheet information - and bent pin FMEA worksheets have a lot of it - so that you never need to enter anything more than once. The result is a far more accurate, consistent, and complete analysis requiring much less effort. It brings bent pin analysis into the 21st century.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"12 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113962111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925761
J. Andrews, D. Prescott, R. Remenyte-Prescott
This paper presents a decision making strategy for autonomous multi-platform systems, wherein a number of platforms perform phased missions in order to achieve an overall mission objective. Phased missions are defined for both single and multi-platform systems and a decision making strategy is outlined for such systems. The requirements for a tool performing such a strategy are discussed and methods and techniques, traditionally used for system reliability assessment, are identified to fulfill these requirements. Two examples are presented in order to demonstrate how a decision making tool would be employed in practice. Finally, a brief discussion of the efficient implementation of such a strategy is presented.
{"title":"A systems reliability approach to decision making in autonomous multi-platform systems operating a phased mission","authors":"J. Andrews, D. Prescott, R. Remenyte-Prescott","doi":"10.1109/RAMS.2008.4925761","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925761","url":null,"abstract":"This paper presents a decision making strategy for autonomous multi-platform systems, wherein a number of platforms perform phased missions in order to achieve an overall mission objective. Phased missions are defined for both single and multi-platform systems and a decision making strategy is outlined for such systems. The requirements for a tool performing such a strategy are discussed and methods and techniques, traditionally used for system reliability assessment, are identified to fulfill these requirements. Two examples are presented in order to demonstrate how a decision making tool would be employed in practice. Finally, a brief discussion of the efficient implementation of such a strategy is presented.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114212075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925821
L. Xing, Wendai Wang
Common-cause failures (CCF) are simultaneous failures of multiple components within a system due to a common-cause or a shared root cause. CCF can contribute significantly to the overall system unreliability. Therefore, it is important to incorporate CCF into the system reliability analysis. Traditional CCF analyses have assumed that the occurrence of a common-cause results in the deterministic/guaranteed failure of components affected by that common-cause. In practical systems, however, the occurrence of a common-cause may result into failures of different components with different probabilities of occurrence. This behavior is termed as probabilistic CCF (PCCF). In this paper, we present a combinatorial method for the reliability analysis of systems subject to PCCF. The approach is represented in a dynamic fault tree model by a proposed probabilistic CCF gate. Basics of the proposed approach and effects of PCCF on the system reliability are illustrated through the detailed quantitative analysis of an example system.
{"title":"Probabilistic common-cause failures analysis","authors":"L. Xing, Wendai Wang","doi":"10.1109/RAMS.2008.4925821","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925821","url":null,"abstract":"Common-cause failures (CCF) are simultaneous failures of multiple components within a system due to a common-cause or a shared root cause. CCF can contribute significantly to the overall system unreliability. Therefore, it is important to incorporate CCF into the system reliability analysis. Traditional CCF analyses have assumed that the occurrence of a common-cause results in the deterministic/guaranteed failure of components affected by that common-cause. In practical systems, however, the occurrence of a common-cause may result into failures of different components with different probabilities of occurrence. This behavior is termed as probabilistic CCF (PCCF). In this paper, we present a combinatorial method for the reliability analysis of systems subject to PCCF. The approach is represented in a dynamic fault tree model by a proposed probabilistic CCF gate. Basics of the proposed approach and effects of PCCF on the system reliability are illustrated through the detailed quantitative analysis of an example system.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125420072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925784
J. Bukowski
This paper proposes a new figure of merit (FOM) for evaluating safety integrity levels (SIL) for safety instrumented systems (SIS). Currently, SIL ratings are based on two separate tables - one for low process demands and one for high process demands. The proposed FOM, probability of an accident as a function of time, PAC(t), unifies the two separate tables into a single table and extends the concept of risk reduction factor (RRF), which is currently only defined for low demand applications, to high demand applications as well. Using PAC(t) as the new FOM explicitly includes the process demand rate in the model and therefore, permits the effects of different demand rates on the safety performance of a specific SIS to be quantified. The model also allows for the inclusion of diagnostic coverage and on-line repair so that the effects of these parameters can also be quantified. Finally, using PAC(t), the maximum time of periodic inspection (TI) permitted before the SIS moves to a lower SIL rating can be easily calculated. A number of examples illustrate the application and usefulness of PAC(t) as the defining FOM for SIL evaluation.
{"title":"A unified model for evaluating the safety integrity level of safety instrumented systems","authors":"J. Bukowski","doi":"10.1109/RAMS.2008.4925784","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925784","url":null,"abstract":"This paper proposes a new figure of merit (FOM) for evaluating safety integrity levels (SIL) for safety instrumented systems (SIS). Currently, SIL ratings are based on two separate tables - one for low process demands and one for high process demands. The proposed FOM, probability of an accident as a function of time, PAC(t), unifies the two separate tables into a single table and extends the concept of risk reduction factor (RRF), which is currently only defined for low demand applications, to high demand applications as well. Using PAC(t) as the new FOM explicitly includes the process demand rate in the model and therefore, permits the effects of different demand rates on the safety performance of a specific SIS to be quantified. The model also allows for the inclusion of diagnostic coverage and on-line repair so that the effects of these parameters can also be quantified. Finally, using PAC(t), the maximum time of periodic inspection (TI) permitted before the SIS moves to a lower SIL rating can be easily calculated. A number of examples illustrate the application and usefulness of PAC(t) as the defining FOM for SIL evaluation.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130631086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925769
T. Halim, L. Tang
The conventional calendar-based mean cumulative function (MCF) plot is useful in monitoring the field reliability of a population of repairable systems deployed in a large quantity. It is simple and easily understood by management. However, it is age-confounded when the system population is heterogeneous with age. Assuming that the systems follow the well-known ldquoBathtubrdquo behavior, the population which consists of a higher proportion of aged systems will perform badly on the MCF plot compared to another population made up of mainly newer systems. Hence, direct comparisons between the two populations may not be fair. This paper illustrates a few simple steps that aid in mitigating such age heterogeneity issue prior to plotting the MCF. The age-adjusted MCF allows a fairer comparison of maintenance performance between the populations. The applicability of the proposed approach is demonstrated using actual field failure data. The case study shows that if differences in system age compositions are not accounted for, different conclusions could be drawn which could be detrimental to the maintenance personnel morale. Worse still, precious maintenance resources might be channeled to the wrong location. Other than age, the proposed approach can be easily extended to adjust for other system attributes.
{"title":"An age-adjusted comparison of field failure data for repairable systems","authors":"T. Halim, L. Tang","doi":"10.1109/RAMS.2008.4925769","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925769","url":null,"abstract":"The conventional calendar-based mean cumulative function (MCF) plot is useful in monitoring the field reliability of a population of repairable systems deployed in a large quantity. It is simple and easily understood by management. However, it is age-confounded when the system population is heterogeneous with age. Assuming that the systems follow the well-known ldquoBathtubrdquo behavior, the population which consists of a higher proportion of aged systems will perform badly on the MCF plot compared to another population made up of mainly newer systems. Hence, direct comparisons between the two populations may not be fair. This paper illustrates a few simple steps that aid in mitigating such age heterogeneity issue prior to plotting the MCF. The age-adjusted MCF allows a fairer comparison of maintenance performance between the populations. The applicability of the proposed approach is demonstrated using actual field failure data. The case study shows that if differences in system age compositions are not accounted for, different conclusions could be drawn which could be detrimental to the maintenance personnel morale. Worse still, precious maintenance resources might be channeled to the wrong location. Other than age, the proposed approach can be easily extended to adjust for other system attributes.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128744433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925807
C. Maisch, B. Bertsche, B. Hohn, H. Otto
This paper deals with an approach for estimating the reliability of transmission oils. Forecasting oil degradation, especially oil oxidation allows to adjust the right oil change intervals in order to save costs and expand the transmission's lifetime. A brief overview about the machine component transmission oil imparts fundamental knowledge. Afterwards definitions of oil failures and combining them to an oil failure system are explained. The oil lifetime line describes the relationship between possible oil temperature and oil lifetime. Such a line is the keystone in order to describe the oil's failure behavior caused by oil oxidation. That's why two approaches are presented to derive an oil lifetime line. Both approaches use a certain oil failure criteria explained in the paper. The first approach is based on the pitting damage accumulation hypothesis. This hypothesis is expanded with the effect of oil degradation what enables to derive an oil lifetime line out of the results of a back-to-back spur gear rig test. Second a General Log Linear Model is used with available data to estimate the gears pitting lifetime depending on oil degradation. With the defined oil failure criteria it was possible to derive an oil lifetime line for mineral oil based fluids. Further work will include the estimation of an oil lifetime line with a probability and confidence intervals. Synthetic oil based fluids need to be investigated more intensive in order to create a suitable oil lifetime line for such fluids.
{"title":"An approach for estimating the reliability of transmission oils","authors":"C. Maisch, B. Bertsche, B. Hohn, H. Otto","doi":"10.1109/RAMS.2008.4925807","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925807","url":null,"abstract":"This paper deals with an approach for estimating the reliability of transmission oils. Forecasting oil degradation, especially oil oxidation allows to adjust the right oil change intervals in order to save costs and expand the transmission's lifetime. A brief overview about the machine component transmission oil imparts fundamental knowledge. Afterwards definitions of oil failures and combining them to an oil failure system are explained. The oil lifetime line describes the relationship between possible oil temperature and oil lifetime. Such a line is the keystone in order to describe the oil's failure behavior caused by oil oxidation. That's why two approaches are presented to derive an oil lifetime line. Both approaches use a certain oil failure criteria explained in the paper. The first approach is based on the pitting damage accumulation hypothesis. This hypothesis is expanded with the effect of oil degradation what enables to derive an oil lifetime line out of the results of a back-to-back spur gear rig test. Second a General Log Linear Model is used with available data to estimate the gears pitting lifetime depending on oil degradation. With the defined oil failure criteria it was possible to derive an oil lifetime line for mineral oil based fluids. Further work will include the estimation of an oil lifetime line with a probability and confidence intervals. Synthetic oil based fluids need to be investigated more intensive in order to create a suitable oil lifetime line for such fluids.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131434276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925768
L. H. Crow
It is common practice for systems to be subjective to operational testing during their development program. The objective of this testing is to evaluate the performance, including reliability, of the system under conditions that represent actual use conditions. Because of expense, resources, schedule, and other considerations, these operational tests rarely represent exactly the actual use conditions. Rather, stated mission profile conditions are specific for the operational testing. These mission profiles conditions are typically general statements that guide the testing on an average basis during the testing. Because of practical constraints the elements that make up the mission profile conditions are typically tested under varying schedules with the intent that on average the mission profile conditions are met. It is also common practice that reliability corrective actions are incorporated into the system during this type of testing. That is, the test is often an operational mission profile reliability growth test. Under these conditions, we usually have a lack of structure for managing the elements that make up the mission profiles, which makes it very difficult to have an agreed-on methodology for estimating the system's reliability. This is especially true if reliability growth is occurring. Many systems fail operational testing because key assessments parameters can not be made in a straightforward clear manner so that management can take timely and appropriate action. This paper addresses this issue and presents a methodology currently being applied on major Department of Defense programs for operational reliability growth testing.
{"title":"A methodology for managing reliability growth during operational mission profile testing","authors":"L. H. Crow","doi":"10.1109/RAMS.2008.4925768","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925768","url":null,"abstract":"It is common practice for systems to be subjective to operational testing during their development program. The objective of this testing is to evaluate the performance, including reliability, of the system under conditions that represent actual use conditions. Because of expense, resources, schedule, and other considerations, these operational tests rarely represent exactly the actual use conditions. Rather, stated mission profile conditions are specific for the operational testing. These mission profiles conditions are typically general statements that guide the testing on an average basis during the testing. Because of practical constraints the elements that make up the mission profile conditions are typically tested under varying schedules with the intent that on average the mission profile conditions are met. It is also common practice that reliability corrective actions are incorporated into the system during this type of testing. That is, the test is often an operational mission profile reliability growth test. Under these conditions, we usually have a lack of structure for managing the elements that make up the mission profiles, which makes it very difficult to have an agreed-on methodology for estimating the system's reliability. This is especially true if reliability growth is occurring. Many systems fail operational testing because key assessments parameters can not be made in a straightforward clear manner so that management can take timely and appropriate action. This paper addresses this issue and presents a methodology currently being applied on major Department of Defense programs for operational reliability growth testing.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129682222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925767
A. P. Patra, P. Soderholm, U. Kumar
Life Cycle Cost (LCC) is used as a cost effective decision support for maintenance of railway track infrastructure. However, a fair degree of uncertainty associated with the estimation of LCC is due to the statistical characteristics of Reliability, Availability and Maintainability (RAM) parameters. This paper illustrates a methodology for estimation of uncertainty linked with LCC, by a combination of Design of Experiment (DoE) and Monte Carlo simulation. The paper also includes developed maintenance cost models for track and a case study of Banverket (Swedish National Rail Administration).
{"title":"Uncertainty in Life Cycle Cost of railway track","authors":"A. P. Patra, P. Soderholm, U. Kumar","doi":"10.1109/RAMS.2008.4925767","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925767","url":null,"abstract":"Life Cycle Cost (LCC) is used as a cost effective decision support for maintenance of railway track infrastructure. However, a fair degree of uncertainty associated with the estimation of LCC is due to the statistical characteristics of Reliability, Availability and Maintainability (RAM) parameters. This paper illustrates a methodology for estimation of uncertainty linked with LCC, by a combination of Design of Experiment (DoE) and Monte Carlo simulation. The paper also includes developed maintenance cost models for track and a case study of Banverket (Swedish National Rail Administration).","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128242508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-01-28DOI: 10.1109/RAMS.2008.4925779
Meng-Lai Yin, R. Arellano
The problem addressed here is the complexity in reliability modeling for network systems with non-independent paths. Dependency usually is dealt with models with high fidelity and high complexity, which leads to the difficulties in model construction and solution. A pivoting method is proposed here to effectively handle the complexity. The presentation starts from the discussion of independent cases, where combinatorial approach such as reliability block diagram method can be applied. Networks with non-independent paths are then addressed, with the pivoting method applied. This approach is applicable to modeling complex systems beyond the example presented here, i.e., network systems with non-independent paths. Any system with components that cause the dependencies can be analyzed using the approach proposed.
{"title":"A case study on network reliability analysis for systems with non-independent paths","authors":"Meng-Lai Yin, R. Arellano","doi":"10.1109/RAMS.2008.4925779","DOIUrl":"https://doi.org/10.1109/RAMS.2008.4925779","url":null,"abstract":"The problem addressed here is the complexity in reliability modeling for network systems with non-independent paths. Dependency usually is dealt with models with high fidelity and high complexity, which leads to the difficulties in model construction and solution. A pivoting method is proposed here to effectively handle the complexity. The presentation starts from the discussion of independent cases, where combinatorial approach such as reliability block diagram method can be applied. Networks with non-independent paths are then addressed, with the pivoting method applied. This approach is applicable to modeling complex systems beyond the example presented here, i.e., network systems with non-independent paths. Any system with components that cause the dependencies can be analyzed using the approach proposed.","PeriodicalId":143940,"journal":{"name":"2008 Annual Reliability and Maintainability Symposium","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132252812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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