Pub Date : 1900-01-01DOI: 10.1109/RAM.2017.7889658
J. Lucas, A. Thiraviam, Ahmed K Elshennawy, Abdulrahman Albar
Many modern companies view reliability as a critical consideration during design, but often fail in achieving the required level of reliability in their products. The reasons for failing to achieve a product line's required reliability are numerous, but it is clear that the lack of proper implementation of an effective reliability program is one of the main drivers for this lack of success. In working with a number of companies that produce products ranging from simple to complex and with a variety of maturities, it is clear that reliebility programs are not “one-size-fits-all”, and rather need to be tailored to a product's complexity and current life cycle maturity. This paper examines products at three different levels of complexity (Low, Medium, and High), and three different levels of maturity (Qualified, Deployed, and Field Proven). Data from product lines at a variety of combinations of these categories have been examined. Results of this analysis indicate that levels of reliability are highly correlated to complexity, with an increase in complexity resulting in a decrease in reliability. Additionally, product line reliability is also observed to increase with product line maturity. Neither of these results were unexpected, but the analysis also indicated that some reliability tools, specifically FMECAs and FRACAS implementation, were most effective in increasing reliability in all product complexity levels, whereas other tools, such as RBDA, were effective in some cases, but had a more limited effectiveness on less complex products.
{"title":"The effectiveness of reliability programs and tools based on design maturity and complexity","authors":"J. Lucas, A. Thiraviam, Ahmed K Elshennawy, Abdulrahman Albar","doi":"10.1109/RAM.2017.7889658","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889658","url":null,"abstract":"Many modern companies view reliability as a critical consideration during design, but often fail in achieving the required level of reliability in their products. The reasons for failing to achieve a product line's required reliability are numerous, but it is clear that the lack of proper implementation of an effective reliability program is one of the main drivers for this lack of success. In working with a number of companies that produce products ranging from simple to complex and with a variety of maturities, it is clear that reliebility programs are not “one-size-fits-all”, and rather need to be tailored to a product's complexity and current life cycle maturity. This paper examines products at three different levels of complexity (Low, Medium, and High), and three different levels of maturity (Qualified, Deployed, and Field Proven). Data from product lines at a variety of combinations of these categories have been examined. Results of this analysis indicate that levels of reliability are highly correlated to complexity, with an increase in complexity resulting in a decrease in reliability. Additionally, product line reliability is also observed to increase with product line maturity. Neither of these results were unexpected, but the analysis also indicated that some reliability tools, specifically FMECAs and FRACAS implementation, were most effective in increasing reliability in all product complexity levels, whereas other tools, such as RBDA, were effective in some cases, but had a more limited effectiveness on less complex products.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124944363","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889760
V. Nagaraju, L. Fiondella
Most software reliability growth models characterize the software process as a function of testing time. However, during the software testing process, the failure data is affected by additional factors such as testing strategy and environment, integration testing, and resource allocation. This will have a major impact on the fault detection process reflecting the effect of such factors at various stages of testing, which are known as changepoints. Recently, several researchers have proposed non-homogeneous Poisson process software reliability models with one or more changepoints to model the data well. However, one of the limitations of previous research is that only homogeneous combinations of failure distributions before and after changepoints are considered. However, in real data sets this is often not the case. This paper develops heterogeneous single changepoint models by considering different failure distributions before and after the changepoint and applies algorithms to maximize the likelihood of these models. Heterogeneous models are compared with existing homogeneous models using goodness-of-fit measures. The expectation conditional maximization algorithm identifies the maximum likelihood estimates of the model parameters. Online changepoint analysis is also described. Experimental results suggest that heterogeneous changepoint models better characterize some failure data sets.
{"title":"A single changepoint software reliability growth model with heterogeneous fault detection processes","authors":"V. Nagaraju, L. Fiondella","doi":"10.1109/RAM.2017.7889760","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889760","url":null,"abstract":"Most software reliability growth models characterize the software process as a function of testing time. However, during the software testing process, the failure data is affected by additional factors such as testing strategy and environment, integration testing, and resource allocation. This will have a major impact on the fault detection process reflecting the effect of such factors at various stages of testing, which are known as changepoints. Recently, several researchers have proposed non-homogeneous Poisson process software reliability models with one or more changepoints to model the data well. However, one of the limitations of previous research is that only homogeneous combinations of failure distributions before and after changepoints are considered. However, in real data sets this is often not the case. This paper develops heterogeneous single changepoint models by considering different failure distributions before and after the changepoint and applies algorithms to maximize the likelihood of these models. Heterogeneous models are compared with existing homogeneous models using goodness-of-fit measures. The expectation conditional maximization algorithm identifies the maximum likelihood estimates of the model parameters. Online changepoint analysis is also described. Experimental results suggest that heterogeneous changepoint models better characterize some failure data sets.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124490565","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889699
Ted Boone, P. Franklin
A cost model for customer premises equipment has been developed. This model enables pinpoint prioritization of operational and reliability improvement efforts.
为客户驻地设备制定了一个成本模型。该模型能够精确地确定操作和可靠性改进工作的优先级。
{"title":"Cost modeling for customer premises equipment","authors":"Ted Boone, P. Franklin","doi":"10.1109/RAM.2017.7889699","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889699","url":null,"abstract":"A cost model for customer premises equipment has been developed. This model enables pinpoint prioritization of operational and reliability improvement efforts.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"29 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550360","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889648
J. Bukowski, W. Goble
According to certain safety standards [1, 2, 3], when assessing the safety performance of a safety instrumented function (SIF) operating in high demand mode, full credit can be given for the positive effects of SIF automatic self-diagnostics (ASD) provided the frequency of self-diagnostic execution is 100 times (100X) or more the demand rate on the SIF and the SIF is configured to convert dangerous failures into safe failures via an automatic shutdown. However, no credit may be given for the positive safety effects of SIF ASD if the frequency of ASD execution is less than 100X the demand rate. This paper shows that the 100X requirement is excessive and that significant positive safety effects accrue even when the ASD frequency is much smaller than the 100X stipulation. The theory, which provides reasonable justification for assigning some degree of partial diagnostic credit (PDC) for SIF ASD based on the ratio of ASD frequency to demand rate, is developed under two different assumptions: Scenario 1 which is extremely conservative and Scenario 2 which is realistic. It is shown that even under the conservative assumption, a frequency of ASD execution of as little as 2X the rate of demand on the SIF deserves at least 60% credit. Under the realistic assumption, the 2X frequency of ASD execution deserves at least 78% credit! Further, ASD execution frequencies of 10X deserve at least 90% credit under the conservative assumption and at least 95% credit under the realistic assumption. These findings suggest that a SIF operating in high demand mode which currently is not receiving credit for its ASD may be reassessed at a lower PDF(t)/hr (a safety metric for SIF in high demand mode) and perhaps a higher safety integrity level (SIL). Furthermore, manufacturers that may have been reluctant to include ASD in equipment used in SIF construction because of the likelihood that the ASD execution frequency would not qualify for PDC in a SIL assessment, may wish to reconsider given that reasonable justification for assigning at least some PDC for the positive effects of ASD is now possible.
{"title":"Properly crediting diagnostics in safety instrumented functions for high demand processes","authors":"J. Bukowski, W. Goble","doi":"10.1109/RAM.2017.7889648","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889648","url":null,"abstract":"According to certain safety standards [1, 2, 3], when assessing the safety performance of a safety instrumented function (SIF) operating in high demand mode, full credit can be given for the positive effects of SIF automatic self-diagnostics (ASD) provided the frequency of self-diagnostic execution is 100 times (100X) or more the demand rate on the SIF and the SIF is configured to convert dangerous failures into safe failures via an automatic shutdown. However, no credit may be given for the positive safety effects of SIF ASD if the frequency of ASD execution is less than 100X the demand rate. This paper shows that the 100X requirement is excessive and that significant positive safety effects accrue even when the ASD frequency is much smaller than the 100X stipulation. The theory, which provides reasonable justification for assigning some degree of partial diagnostic credit (PDC) for SIF ASD based on the ratio of ASD frequency to demand rate, is developed under two different assumptions: Scenario 1 which is extremely conservative and Scenario 2 which is realistic. It is shown that even under the conservative assumption, a frequency of ASD execution of as little as 2X the rate of demand on the SIF deserves at least 60% credit. Under the realistic assumption, the 2X frequency of ASD execution deserves at least 78% credit! Further, ASD execution frequencies of 10X deserve at least 90% credit under the conservative assumption and at least 95% credit under the realistic assumption. These findings suggest that a SIF operating in high demand mode which currently is not receiving credit for its ASD may be reassessed at a lower PDF(t)/hr (a safety metric for SIF in high demand mode) and perhaps a higher safety integrity level (SIL). Furthermore, manufacturers that may have been reluctant to include ASD in equipment used in SIF construction because of the likelihood that the ASD execution frequency would not qualify for PDC in a SIL assessment, may wish to reconsider given that reasonable justification for assigning at least some PDC for the positive effects of ASD is now possible.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124607453","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889733
Wendai Wang
Carefully planning reliability testing is necessary for success of a product development. Sample size determination is an important step in test planning. One of most common questions any reliability engineer gets asked is “how many units do we need to test?” Of course the answer depends on a number of factors and information in hand. The design of reliability demonstration testing (RDT) has been widely studied by many researchers. Most planning methods are based on the time-to-failure properties of product under test, such as the Binomial equation, the Chi-Squared formula, and etc. However, quite often, reliability test requirements are defined by certain performance characteristic(s), or physical characteristic(s), or quality characteristic(s). Very few works have been published to plan a reliability test with performance measurements directly. Some works on degradation measurements analysis, including degradation test plan for Wiener degradation processes, have been carried out for maintenance optimization purpose. This paper develops a test planning method for reliability demonstration test when the reliability test requirement is constructed with its performance or degradation measurements. A simple formula for sample size determination is provided in the paper, and a couple of case studies will be presented to help reliability practitioners to plan the reliability testing using the proposed method.
{"title":"Planning reliability demonstration test with performance requirements","authors":"Wendai Wang","doi":"10.1109/RAM.2017.7889733","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889733","url":null,"abstract":"Carefully planning reliability testing is necessary for success of a product development. Sample size determination is an important step in test planning. One of most common questions any reliability engineer gets asked is “how many units do we need to test?” Of course the answer depends on a number of factors and information in hand. The design of reliability demonstration testing (RDT) has been widely studied by many researchers. Most planning methods are based on the time-to-failure properties of product under test, such as the Binomial equation, the Chi-Squared formula, and etc. However, quite often, reliability test requirements are defined by certain performance characteristic(s), or physical characteristic(s), or quality characteristic(s). Very few works have been published to plan a reliability test with performance measurements directly. Some works on degradation measurements analysis, including degradation test plan for Wiener degradation processes, have been carried out for maintenance optimization purpose. This paper develops a test planning method for reliability demonstration test when the reliability test requirement is constructed with its performance or degradation measurements. A simple formula for sample size determination is provided in the paper, and a couple of case studies will be presented to help reliability practitioners to plan the reliability testing using the proposed method.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122301897","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889703
C. Drake, D. Ray
Using a static Sensitivity Test approach, and analyzing the collected data using Binary and Ordinal Logistic Regression, the risk of potentially falsely inducing weapon damage, either in a latent or fully realized manner, was effectively managed and mitigated while simultaneously providing the Army with a more adequate proof cartridge for 5.56mm weapons including the M4 carbine, M16 rifle, and M249 Squad Automatic Weapon. By incorporating error propagation through Monte Carlo simulation, robust tolerances were derived using the Binary Logistic Regression model to estimate the pressure value which corresponded to a target probability of encountering a critical defect threshold of 0.000001, or 1 in a million.
{"title":"Risk management of a high pressured test cartridge using sensitivity testing","authors":"C. Drake, D. Ray","doi":"10.1109/RAM.2017.7889703","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889703","url":null,"abstract":"Using a static Sensitivity Test approach, and analyzing the collected data using Binary and Ordinal Logistic Regression, the risk of potentially falsely inducing weapon damage, either in a latent or fully realized manner, was effectively managed and mitigated while simultaneously providing the Army with a more adequate proof cartridge for 5.56mm weapons including the M4 carbine, M16 rifle, and M249 Squad Automatic Weapon. By incorporating error propagation through Monte Carlo simulation, robust tolerances were derived using the Binary Logistic Regression model to estimate the pressure value which corresponded to a target probability of encountering a critical defect threshold of 0.000001, or 1 in a million.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129505495","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889690
J. Pulido, J. Klinger, W. Hill
As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which the design is maturing; while classical qualitative methods do not provide the level of detail and granularity required by the designers to make high-quality risk informed decisions. Every company is dependent on some type of asset that keeps the business in business — be it a computer, a centrifuge or a megawatt transformer. In a large enterprise, reducing costs related to asset maintenance, repair and ultimate replacement is at the top of management concerns [1]. Downtime in any network, manufacturing or computer system ultimately results not only in high repair costs, but in customer dissatisfaction and lower potential sales. In response to these concerns, this paper presents a methodology for using Life Data Analysis (LDA) techniques for evaluating new product innovation and projecting product performance due to several failure modes. The paper presents an application for the airline industry where the technique was used in determining the right failure mode as well as enable the program to compare improvements to the fleet.
{"title":"Life data analysis with applications to aircraft modeling","authors":"J. Pulido, J. Klinger, W. Hill","doi":"10.1109/RAM.2017.7889690","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889690","url":null,"abstract":"As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which the design is maturing; while classical qualitative methods do not provide the level of detail and granularity required by the designers to make high-quality risk informed decisions. Every company is dependent on some type of asset that keeps the business in business — be it a computer, a centrifuge or a megawatt transformer. In a large enterprise, reducing costs related to asset maintenance, repair and ultimate replacement is at the top of management concerns [1]. Downtime in any network, manufacturing or computer system ultimately results not only in high repair costs, but in customer dissatisfaction and lower potential sales. In response to these concerns, this paper presents a methodology for using Life Data Analysis (LDA) techniques for evaluating new product innovation and projecting product performance due to several failure modes. The paper presents an application for the airline industry where the technique was used in determining the right failure mode as well as enable the program to compare improvements to the fleet.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132454816","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889770
Rodney Benson, Darryl W. Kellner
Aircraft manufacturers and their suppliers are required by the Federal Aviation Administration to perform special safety analyses of equipment installed within the fuel tank zone of aircraft. These analyses are required to verify the design is sufficiently safe regarding the prevention of ignition of fuel vapors during operations. The following provides guidance on a method that has successfully been used to document the results of a safety analysis performed to satisfy these requirements and complies with industry guidance. A block diagram of the safety analysis process that includes data flow from other sources is provided and explained. A simplified example is provided to walk through the steps performed during the analysis process.
{"title":"Effective application of ignition risk safety analysis","authors":"Rodney Benson, Darryl W. Kellner","doi":"10.1109/RAM.2017.7889770","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889770","url":null,"abstract":"Aircraft manufacturers and their suppliers are required by the Federal Aviation Administration to perform special safety analyses of equipment installed within the fuel tank zone of aircraft. These analyses are required to verify the design is sufficiently safe regarding the prevention of ignition of fuel vapors during operations. The following provides guidance on a method that has successfully been used to document the results of a safety analysis performed to satisfy these requirements and complies with industry guidance. A block diagram of the safety analysis process that includes data flow from other sources is provided and explained. A simplified example is provided to walk through the steps performed during the analysis process.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134203042","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889713
C. Gu, Yihai He, Xiao Han, M. Xie
In this paper, a comprehensive cost oriented dynamic predictive maintenance policy based on mission reliability state is developed for a multi-state single-machine manufacturing system. In view of the inherent polymorphism of manufacturing systems (i.e., dynamic production scheduling and performance degradation), the connotation of mission reliability of equipment is defined and modeled based on the processing capacity distribution which integrates multiple fault data. Further, the relationship between mission reliability and performance of equipment is established by using the unavailability as the intermediary. The optimal predictive maintenance policy, the best mission reliability threshold for performing predictive maintenance action, is obtained by minimizing the comprehensive cost which includes processing capacity loss, corrective maintenance cost, predictive maintenance cost and indirect loss caused by failing to meet due dates over the planning period. This paper will also evaluate a manufacturing system of the cylinder head of an automotive engine as a case study to illustrate the effectiveness and advantages of the proposed method. The final result shows that a more significant economic benefit can be achieved by the proposed approach, which considers the mission reliability and comprehensive cost relative to the periodic preventive maintenance policy.
{"title":"Comprehensive cost oriented predictive maintenance based on mission reliability for a manufacturing system","authors":"C. Gu, Yihai He, Xiao Han, M. Xie","doi":"10.1109/RAM.2017.7889713","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889713","url":null,"abstract":"In this paper, a comprehensive cost oriented dynamic predictive maintenance policy based on mission reliability state is developed for a multi-state single-machine manufacturing system. In view of the inherent polymorphism of manufacturing systems (i.e., dynamic production scheduling and performance degradation), the connotation of mission reliability of equipment is defined and modeled based on the processing capacity distribution which integrates multiple fault data. Further, the relationship between mission reliability and performance of equipment is established by using the unavailability as the intermediary. The optimal predictive maintenance policy, the best mission reliability threshold for performing predictive maintenance action, is obtained by minimizing the comprehensive cost which includes processing capacity loss, corrective maintenance cost, predictive maintenance cost and indirect loss caused by failing to meet due dates over the planning period. This paper will also evaluate a manufacturing system of the cylinder head of an automotive engine as a case study to illustrate the effectiveness and advantages of the proposed method. The final result shows that a more significant economic benefit can be achieved by the proposed approach, which considers the mission reliability and comprehensive cost relative to the periodic preventive maintenance policy.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134431752","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 : 1900-01-01DOI: 10.1109/RAM.2017.7889744
J. Pulido, M. Bride, M. Fonseca
Environmental and Operational Stress Testing is the most common approach to precipitating structure latent defects before the manufacturing of products. This testing consists of applying environmentally induced stresses to the product. Typically, these environmental stresses for mechanical structural automotive components consist of vibration loading based on road input and/or self-induced vibration with cycling temperatures between a high and low extreme. Many components in most fields of engineering are subjected to fatigue at elevated temperatures. High — temperature fatigue is mainly a concern at temperatures above 30 or 40 percent of the absolute melting temperature. Since some of these components are costly and safety-critical, it is understandable that there is a significant interest in proper characterization of fatigue behavior at high temperatures. In most cases strain life characteristic is not known for a given application and or a given material. To further complicate matters, the component application can be in an environment where more than one failure mode due to the application type can be observed. This paper presents a practical testing methodology used to determine the product's operational life given high temperature operational application and the results are compared with field observations.
{"title":"Reliability analysis of igniters under thermal mechanical loadings","authors":"J. Pulido, M. Bride, M. Fonseca","doi":"10.1109/RAM.2017.7889744","DOIUrl":"https://doi.org/10.1109/RAM.2017.7889744","url":null,"abstract":"Environmental and Operational Stress Testing is the most common approach to precipitating structure latent defects before the manufacturing of products. This testing consists of applying environmentally induced stresses to the product. Typically, these environmental stresses for mechanical structural automotive components consist of vibration loading based on road input and/or self-induced vibration with cycling temperatures between a high and low extreme. Many components in most fields of engineering are subjected to fatigue at elevated temperatures. High — temperature fatigue is mainly a concern at temperatures above 30 or 40 percent of the absolute melting temperature. Since some of these components are costly and safety-critical, it is understandable that there is a significant interest in proper characterization of fatigue behavior at high temperatures. In most cases strain life characteristic is not known for a given application and or a given material. To further complicate matters, the component application can be in an environment where more than one failure mode due to the application type can be observed. This paper presents a practical testing methodology used to determine the product's operational life given high temperature operational application and the results are compared with field observations.","PeriodicalId":138871,"journal":{"name":"2017 Annual Reliability and Maintainability Symposium (RAMS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114867801","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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