Pub Date : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153616
Z. Li, Dong Xu
One challenge in reliability growth modeling is the estimation of initial failure intensities of the new design units under reliability growth testing. In existing literature, the failure intensities are usually estimated based expert knowledge and complexity and similarity analysis between new designs and mature existing product designs. Such estimations are mostly assumed to be fixed even though unknown. Likewise, the final projected reliability is estimated under a fixed growth rate according to the characteristics of the new design. Existing reliability growth models have not well incorporated the uncertainty in initial failure intensity estimation due to limited testing data of new design contents, and the uncertainty of growth rate determined by reliability improvement program effectiveness and manufacturing processes along with other supporting functions. This research proposes to model the initial failure intensity with probabilistic models such as gamma distributions, and the growth rate is modeled as a random effect in the log-log reliability growth model. Under such a modeling framework, both failure intensity and growth rate can be continuously updated as more testing and operations data become available. Such a Bayesian reliability growth modeling approach can deal with both uncertainties in failure rate and growth rate estimations.
{"title":"A Bayesian Approach for Modeling Reliability Growth","authors":"Z. Li, Dong Xu","doi":"10.1109/RAMS48030.2020.9153616","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153616","url":null,"abstract":"One challenge in reliability growth modeling is the estimation of initial failure intensities of the new design units under reliability growth testing. In existing literature, the failure intensities are usually estimated based expert knowledge and complexity and similarity analysis between new designs and mature existing product designs. Such estimations are mostly assumed to be fixed even though unknown. Likewise, the final projected reliability is estimated under a fixed growth rate according to the characteristics of the new design. Existing reliability growth models have not well incorporated the uncertainty in initial failure intensity estimation due to limited testing data of new design contents, and the uncertainty of growth rate determined by reliability improvement program effectiveness and manufacturing processes along with other supporting functions. This research proposes to model the initial failure intensity with probabilistic models such as gamma distributions, and the growth rate is modeled as a random effect in the log-log reliability growth model. Under such a modeling framework, both failure intensity and growth rate can be continuously updated as more testing and operations data become available. Such a Bayesian reliability growth modeling approach can deal with both uncertainties in failure rate and growth rate estimations.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114995228","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153708
M. Hecht, Aaron Chuidian, Taiki Tanaka, Ross Raymond
Summary & ConclusionsIn this paper, an automated FMEA generation capability using the SysML modeling language and described its application to a simple SCADA computer network was described. The outputs produced by the tool (implemented as a SysML plug-in) from this analysis were presented, and the resultant insights into the design were described. The fundamental innovation in our approach is the identification and enumeration of all failure propagation paths and the detailed documentation of the failure transformations, detection measures, mitigation measures and protective measures that can be applied to these devices to prevent or mitigate the impact of the anomaly. By doing so, we can expand the traditional FMEA approach to analysis of cyberattack vectors. Because our approach is automated and can be readily integrated into a system development effort using Model Based Systems Engineering (MBSE), the analysis can be readily repeated throughout the design and can be used frequently to assess a system design, identify weaknesses, and take corrective actions to create a more resilient and robust system
{"title":"Automated Generation of FMEAs using SysML for Reliability, Safety, and Cybersecurity","authors":"M. Hecht, Aaron Chuidian, Taiki Tanaka, Ross Raymond","doi":"10.1109/RAMS48030.2020.9153708","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153708","url":null,"abstract":"Summary & ConclusionsIn this paper, an automated FMEA generation capability using the SysML modeling language and described its application to a simple SCADA computer network was described. The outputs produced by the tool (implemented as a SysML plug-in) from this analysis were presented, and the resultant insights into the design were described. The fundamental innovation in our approach is the identification and enumeration of all failure propagation paths and the detailed documentation of the failure transformations, detection measures, mitigation measures and protective measures that can be applied to these devices to prevent or mitigate the impact of the anomaly. By doing so, we can expand the traditional FMEA approach to analysis of cyberattack vectors. Because our approach is automated and can be readily integrated into a system development effort using Model Based Systems Engineering (MBSE), the analysis can be readily repeated throughout the design and can be used frequently to assess a system design, identify weaknesses, and take corrective actions to create a more resilient and robust system","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126624926","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153639
J. Schwendler, Chris Kang, Dan Worts
Corner-case: a definable use case or test case that challenges a complex system up to or beyond specification, usually with concurrent stress factor imposition.
{"title":"Challenge and Response for Corner-Case Robustness Improvement","authors":"J. Schwendler, Chris Kang, Dan Worts","doi":"10.1109/RAMS48030.2020.9153639","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153639","url":null,"abstract":"Corner-case: a definable use case or test case that challenges a complex system up to or beyond specification, usually with concurrent stress factor imposition.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115061112","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153666
Qunyong Wang, Hua Bai, Dongmei Chen, Xupeng Sun
In this paper, a theory and method for rapidly obtaining the degradation trend life test of sensitive parameters is introduced, which is suitable for the rapid test and evaluation of the life of electronic components. The theory of life data analysis comes from the exploratory data method (EDA),. The technical realization of rapidly obtaining the degradation trend of sensitive parameters depends on reducing the interference of test stress fluctuation to the measurement under the condition ofhigh stability test stress, and at the same time, the degradation sensitive parameters of the tested products are measured with high precision. The measured data are collected at high speed, and the degradation model of sensitive parameters with time is established on-line, and the extrapolation life of the sample is calculated according to the degradation model. For integrated circuit products, we have developed the corresponding test verification system, carried out the SRAM standby life and FPGA working life of limited samples, and explored the possibility of rapidly obtaining the degradation trend of sensitive parameters in the test method. It lays a foundation for further practical research in the future.
{"title":"A Life Test Method for Rapidly Obtaining the Degradation Trend of Sensitive Parameters","authors":"Qunyong Wang, Hua Bai, Dongmei Chen, Xupeng Sun","doi":"10.1109/RAMS48030.2020.9153666","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153666","url":null,"abstract":"In this paper, a theory and method for rapidly obtaining the degradation trend life test of sensitive parameters is introduced, which is suitable for the rapid test and evaluation of the life of electronic components. The theory of life data analysis comes from the exploratory data method (EDA),. The technical realization of rapidly obtaining the degradation trend of sensitive parameters depends on reducing the interference of test stress fluctuation to the measurement under the condition ofhigh stability test stress, and at the same time, the degradation sensitive parameters of the tested products are measured with high precision. The measured data are collected at high speed, and the degradation model of sensitive parameters with time is established on-line, and the extrapolation life of the sample is calculated according to the degradation model. For integrated circuit products, we have developed the corresponding test verification system, carried out the SRAM standby life and FPGA working life of limited samples, and explored the possibility of rapidly obtaining the degradation trend of sensitive parameters in the test method. It lays a foundation for further practical research in the future.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114406360","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153618
T. Myklebust, T. Stålhane, G. Jenssen, I. Wærø
Today’s world of road traffic is dramatically changing, triggered by the development of new technologies and a focus on accident-free driving. “Autonomous” cars are being tested several places. It is a race, among the car manufacturers, to be among the first to develop fully autonomous cars and authorities are supporting them by adapting the regulations. New technology has made it simpler to monitor the operation of cars, including their safety systems. A safety case is required by the international standard for road vehicles, ISO 26262:2018 series. UK has issued a “Code of practice” that also requires a safety case to be issued. The practice states that trialing organizations should develop an abridged public version of the safety case that should be freely available. UL (Underwriters Laboratories) a USA certification and standards development company plan to issue a new standard UL4600 in 2019 that addresses safety case for the safety of autonomous products. However, when accidents related to autonomous cars happen, minor discussions have taken place in media related to the safety evidence supplied by the car manufacturer, presented as e.g., a safety case. A safety case is normally developed to convince a third party that the product or system is safe. Our suggestion is that also a safety case for the public should be issued to ensure that (1) the public are aware that safety evidence exists, and (2) that limitations are transparent and described in an easy-to-understand way. Regulations and safety standards will provide requirements and guidelines for manufacturers, third parties and technology developers. It is, however, also important to inform the public. A safety case as it is today is too technical for the public, is often lengthy (more than 100 pages) and includes confidential information, and as a result the safety case cannot be presented to the public. A recent study, March 2019 [21], by the American Automobile Association has found that Americans remain highly skeptical to self-driving vehicles, with nearly three out of four of those surveyed saying they would be afraid to get into a driverless vehicle. We have studied the 16 existing NHTSA (National Highway Traffic Safety Administration) related self-assessment information from manufacturers. None of the reports refer to a safety case, only one report mentions safety case. Based upon these evaluations and our survey, we have suggested a public safety case with a limited number of pages, using concise, easy to read and understandable text, marks and pictures. Using such a safety case will help manufacturers, operators and early implementation sites to gain public trust.
{"title":"Autonomous Cars, Trust and Safety Case for the Public","authors":"T. Myklebust, T. Stålhane, G. Jenssen, I. Wærø","doi":"10.1109/RAMS48030.2020.9153618","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153618","url":null,"abstract":"Today’s world of road traffic is dramatically changing, triggered by the development of new technologies and a focus on accident-free driving. “Autonomous” cars are being tested several places. It is a race, among the car manufacturers, to be among the first to develop fully autonomous cars and authorities are supporting them by adapting the regulations. New technology has made it simpler to monitor the operation of cars, including their safety systems. A safety case is required by the international standard for road vehicles, ISO 26262:2018 series. UK has issued a “Code of practice” that also requires a safety case to be issued. The practice states that trialing organizations should develop an abridged public version of the safety case that should be freely available. UL (Underwriters Laboratories) a USA certification and standards development company plan to issue a new standard UL4600 in 2019 that addresses safety case for the safety of autonomous products. However, when accidents related to autonomous cars happen, minor discussions have taken place in media related to the safety evidence supplied by the car manufacturer, presented as e.g., a safety case. A safety case is normally developed to convince a third party that the product or system is safe. Our suggestion is that also a safety case for the public should be issued to ensure that (1) the public are aware that safety evidence exists, and (2) that limitations are transparent and described in an easy-to-understand way. Regulations and safety standards will provide requirements and guidelines for manufacturers, third parties and technology developers. It is, however, also important to inform the public. A safety case as it is today is too technical for the public, is often lengthy (more than 100 pages) and includes confidential information, and as a result the safety case cannot be presented to the public. A recent study, March 2019 [21], by the American Automobile Association has found that Americans remain highly skeptical to self-driving vehicles, with nearly three out of four of those surveyed saying they would be afraid to get into a driverless vehicle. We have studied the 16 existing NHTSA (National Highway Traffic Safety Administration) related self-assessment information from manufacturers. None of the reports refer to a safety case, only one report mentions safety case. Based upon these evaluations and our survey, we have suggested a public safety case with a limited number of pages, using concise, easy to read and understandable text, marks and pictures. Using such a safety case will help manufacturers, operators and early implementation sites to gain public trust.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129870418","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153678
A. Grundler, M. Dazer, B. Bertsche
To demonstrate the reliability of a product, engineers are forced to find the best feasible compromise between cost, time, and accuracy. In addition, the test configuration must be set according to the lowest possible resource requirements. The approach proposed in this paper utilizes the concept of probability of test success presented by Dazer et al. [1] to assess different test plans. In addition to the probability of test success, the test time and costs are used in the assessment. In order to obtain the distribution of the probability of test success, costs, and time, the different test types are simulated on the respective system levels using a Monte Carlo simulation. Two-parameter Weibull distributions of the failure mechanisms of the system serve as a prerequisite for the simulation. For real-world application, these can stem from similar products and applications, previous product generations, preliminary tests, expert knowledge, or even simulations. Based on these distributions, pseudo-random numbers of failure times are generated.
{"title":"Reliability-Test Planning Considering Multiple Failure Mechanisms and System Levels – an Approach for Identifying the Optimal System-Test Level, Type, and Configuration with Regard to Individual Cost and Time Constraints","authors":"A. Grundler, M. Dazer, B. Bertsche","doi":"10.1109/RAMS48030.2020.9153678","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153678","url":null,"abstract":"To demonstrate the reliability of a product, engineers are forced to find the best feasible compromise between cost, time, and accuracy. In addition, the test configuration must be set according to the lowest possible resource requirements. The approach proposed in this paper utilizes the concept of probability of test success presented by Dazer et al. [1] to assess different test plans. In addition to the probability of test success, the test time and costs are used in the assessment. In order to obtain the distribution of the probability of test success, costs, and time, the different test types are simulated on the respective system levels using a Monte Carlo simulation. Two-parameter Weibull distributions of the failure mechanisms of the system serve as a prerequisite for the simulation. For real-world application, these can stem from similar products and applications, previous product generations, preliminary tests, expert knowledge, or even simulations. Based on these distributions, pseudo-random numbers of failure times are generated.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"1923 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128711284","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153672
O. Blancke, Gabriel McCarthy, Mathieu Payette, L. Bibeau, Jean-François Boudreau, A. Côté, D. Komljenovic, D. Komljenovic, B. Souilah
The paper presents an approach regarding the reliability estimation of complex repairable equipment of electrical utilities. Large quantities of maintenance data have been acquired over the past decades through maintenance data collecting systems. Before using the data, attention must be paid to the uncertainties in data and biases regarding the reliability estimates they generate. The aim of this paper is to propose a novel methodology regarding reliability assessment and evaluation of critical repairable equipment to support maintenance strategy considering uncertain maintenance data. The method integrates two different statistical models for analyzing historical failure data considering their uncertainties. A new validation framework is proposed to evaluate model performance considering those uncertainties. A case study is presented for Hydro-Québec’s major transmission equipment. The limits of the models and their dependability on information uncertainty are discussed.
{"title":"Performance of Reliability Models for Repairable Systems: Dealing with Information Uncertainty","authors":"O. Blancke, Gabriel McCarthy, Mathieu Payette, L. Bibeau, Jean-François Boudreau, A. Côté, D. Komljenovic, D. Komljenovic, B. Souilah","doi":"10.1109/RAMS48030.2020.9153672","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153672","url":null,"abstract":"The paper presents an approach regarding the reliability estimation of complex repairable equipment of electrical utilities. Large quantities of maintenance data have been acquired over the past decades through maintenance data collecting systems. Before using the data, attention must be paid to the uncertainties in data and biases regarding the reliability estimates they generate. The aim of this paper is to propose a novel methodology regarding reliability assessment and evaluation of critical repairable equipment to support maintenance strategy considering uncertain maintenance data. The method integrates two different statistical models for analyzing historical failure data considering their uncertainties. A new validation framework is proposed to evaluate model performance considering those uncertainties. A case study is presented for Hydro-Québec’s major transmission equipment. The limits of the models and their dependability on information uncertainty are discussed.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129896316","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153615
Allura B. Jackson, T. Jackson, Kristella B. Jackson
In August 2015, the second edition of AIAA Standard S-102.2.4-2015, Capability-based FMECA Requirements [1], was released for sale in the public domain. Upon its release, this document became the world’s best FMECA standard, according to the US Army Redstone Arsenal Logistics Support Activity (LOGSA) Division. Three years earlier, a civil servant at LOGSA named Mr. David Hawthorne, was assigned to head a team of government FMECA experts that would evaluate several commercial FMECA standards there were well-known at the time. Metaphorically, this government team had marching orders to down-select to one, the number of commercial FMECA standards that can be easily updated to meet the US Army’s weapons acquisition needs. When this evaluation concluded, the government team’s consensus recommendation was to update the ANSI/AIAA Standard, S-102.2.4-2009: Performance-based FMECA Requirements, to meet the US Army’s weapons acquisition needs.
{"title":"Chronology of Continuous Improvement of the World’s Best FMECA Standard","authors":"Allura B. Jackson, T. Jackson, Kristella B. Jackson","doi":"10.1109/RAMS48030.2020.9153615","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153615","url":null,"abstract":"In August 2015, the second edition of AIAA Standard S-102.2.4-2015, Capability-based FMECA Requirements [1], was released for sale in the public domain. Upon its release, this document became the world’s best FMECA standard, according to the US Army Redstone Arsenal Logistics Support Activity (LOGSA) Division. Three years earlier, a civil servant at LOGSA named Mr. David Hawthorne, was assigned to head a team of government FMECA experts that would evaluate several commercial FMECA standards there were well-known at the time. Metaphorically, this government team had marching orders to down-select to one, the number of commercial FMECA standards that can be easily updated to meet the US Army’s weapons acquisition needs. When this evaluation concluded, the government team’s consensus recommendation was to update the ANSI/AIAA Standard, S-102.2.4-2009: Performance-based FMECA Requirements, to meet the US Army’s weapons acquisition needs.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114193664","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153623
D. Fernald
Software is an important part of the capability drivers for many modern United States Army systems. The importance of improved software system safety processes are highlighted in the last revision to Military Standard (MIL-STD)-882. MILSTD-882E added software system safety techniques and practices. However, many Army systems pre-date the current revision. This paper provides an overview of how the Army Air Defense community is applying the software system safety guidance and techniques to an Air and Missile Defense system. The Patriot Air and Missile Defense (AMD) system is used for the case study. The case study illustrates the process and demonstrate safety analysis effectiveness. As part of the case study there is a discussion of the various Army safety organizations and the synergies between them.
{"title":"U.S. Army Software System Safety Process, Case-Study, and Success Stories","authors":"D. Fernald","doi":"10.1109/RAMS48030.2020.9153623","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153623","url":null,"abstract":"Software is an important part of the capability drivers for many modern United States Army systems. The importance of improved software system safety processes are highlighted in the last revision to Military Standard (MIL-STD)-882. MILSTD-882E added software system safety techniques and practices. However, many Army systems pre-date the current revision. This paper provides an overview of how the Army Air Defense community is applying the software system safety guidance and techniques to an Air and Missile Defense system. The Patriot Air and Missile Defense (AMD) system is used for the case study. The case study illustrates the process and demonstrate safety analysis effectiveness. As part of the case study there is a discussion of the various Army safety organizations and the synergies between them.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121481409","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 : 2020-01-01DOI: 10.1109/RAMS48030.2020.9153694
A. Apostolidis, M. Pelt, K. Stamoulis
Summary & ConclusionsAs every new generation of civil aircraft creates more on-wing data and fleets gradually become more connected with the ground, an increased number of opportunities can be identified for more effective Maintenance, Repair and Overhaul (MRO) operations. Data are becoming a valuable asset for aircraft operators. Sensors measure and record thousands of parameters in increased sampling rates. However, data do not serve any purpose per se. It is the analysis that unleashes their value. Data analytics methods can be simple, making use of visualizations, or more complex, with the use of sophisticated statistics and Artificial Intelligence algorithms. Every problem needs to be approached with the most suitable and less complex method. In MRO operations, two major categories of on-wing data analytics problems can be identified. The first one requires the identification of patterns, which enable the classification and optimization of different maintenance and overhaul processes. The second category of problems requires the identification of rare events, such as the unexpected failure of parts. This cluster of problems relies on the detection of meaningful outliers in large data sets. Different Machine Learning methods can be suggested here, such as Isolation Forest and Logistic Regression. In general, the use of data analytics for maintenance or failure prediction is a scientific field with a great potentiality. Due to its complex nature, the opportunities for aviation Data Analytics in MRO operations are numerous. As MRO services focus increasingly in long term contracts, maintenance organizations with the right forecasting methods will have an advantage. Data accessibility and data quality are two key-factors. At the same time, numerous technical developments related to data transfer and data processing can be promising for the future.
{"title":"Aviation Data Analytics in MRO Operations: Prospects and Pitfalls","authors":"A. Apostolidis, M. Pelt, K. Stamoulis","doi":"10.1109/RAMS48030.2020.9153694","DOIUrl":"https://doi.org/10.1109/RAMS48030.2020.9153694","url":null,"abstract":"Summary & ConclusionsAs every new generation of civil aircraft creates more on-wing data and fleets gradually become more connected with the ground, an increased number of opportunities can be identified for more effective Maintenance, Repair and Overhaul (MRO) operations. Data are becoming a valuable asset for aircraft operators. Sensors measure and record thousands of parameters in increased sampling rates. However, data do not serve any purpose per se. It is the analysis that unleashes their value. Data analytics methods can be simple, making use of visualizations, or more complex, with the use of sophisticated statistics and Artificial Intelligence algorithms. Every problem needs to be approached with the most suitable and less complex method. In MRO operations, two major categories of on-wing data analytics problems can be identified. The first one requires the identification of patterns, which enable the classification and optimization of different maintenance and overhaul processes. The second category of problems requires the identification of rare events, such as the unexpected failure of parts. This cluster of problems relies on the detection of meaningful outliers in large data sets. Different Machine Learning methods can be suggested here, such as Isolation Forest and Logistic Regression. In general, the use of data analytics for maintenance or failure prediction is a scientific field with a great potentiality. Due to its complex nature, the opportunities for aviation Data Analytics in MRO operations are numerous. As MRO services focus increasingly in long term contracts, maintenance organizations with the right forecasting methods will have an advantage. Data accessibility and data quality are two key-factors. At the same time, numerous technical developments related to data transfer and data processing can be promising for the future.","PeriodicalId":360096,"journal":{"name":"2020 Annual Reliability and Maintainability Symposium (RAMS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114812370","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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