Pub Date : 1995-01-16DOI: 10.1109/RAMS.1995.513234
D. D. Bell
A comparison is made between the defense driven aerospace industry and the medical device industry with respect to their approach to achieving reliability. The Department of Defense establishment has driven the aerospace industry to consider and analyze reliability through imposing a complex set of standards and specifications that control all aspects of design and analysis. The medical device industry, driven by market forces, safety considerations, and limited government regulation, has typically lagged in the imposition of specific reliability requirements and performance of reliability analyses in the design and development process. This situation is changing, the Department of Defense is adopting more and more commercial standards and the medical device industry is responding to a marketplace that is becoming more demanding, where commercial standards and specifications are becoming more widely imposed, and where the Federal, state, and local governments are becoming more active in exerting influence on the industry. The net result is an increasing similarity in the approach taken by of the aerospace and medical device industries towards achieving reliability.
{"title":"Contrasting the medical-device and aerospace-industries approach to reliability","authors":"D. D. Bell","doi":"10.1109/RAMS.1995.513234","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513234","url":null,"abstract":"A comparison is made between the defense driven aerospace industry and the medical device industry with respect to their approach to achieving reliability. The Department of Defense establishment has driven the aerospace industry to consider and analyze reliability through imposing a complex set of standards and specifications that control all aspects of design and analysis. The medical device industry, driven by market forces, safety considerations, and limited government regulation, has typically lagged in the imposition of specific reliability requirements and performance of reliability analyses in the design and development process. This situation is changing, the Department of Defense is adopting more and more commercial standards and the medical device industry is responding to a marketplace that is becoming more demanding, where commercial standards and specifications are becoming more widely imposed, and where the Federal, state, and local governments are becoming more active in exerting influence on the industry. The net result is an increasing similarity in the approach taken by of the aerospace and medical device industries towards achieving reliability.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125754003","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513216
B. Mitchell, R.J. Murry
The United States Department of Energy (DOE) Strategic Petroleum Reserve (SPR) has one of the country's largest and most diverse collection of large pumps and motors. These pumps and motors, along with their power, control, and valving support systems, are used to move the enormous quantities of crude oil stored within the reserve. A predictive maintenance program (PdM) was initiated on the SPR during 1993 and 1994. During the development, implementation, and early phases of the PdM program, the program evolved based on lessons learned. The primary areas of involvement and potential improvement in the process are: defining the PdM program based on project needs; obtaining and maintaining support for the program; setting realistic implementation goals and schedules; establishing and justifying manpower levels; developing and involving a project team in the program; developing detailed equipment specifications; identifying training requirements; implementing a phased program; and developing project reporting schemes.
{"title":"Predictive maintenance program evolution-lessons learned","authors":"B. Mitchell, R.J. Murry","doi":"10.1109/RAMS.1995.513216","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513216","url":null,"abstract":"The United States Department of Energy (DOE) Strategic Petroleum Reserve (SPR) has one of the country's largest and most diverse collection of large pumps and motors. These pumps and motors, along with their power, control, and valving support systems, are used to move the enormous quantities of crude oil stored within the reserve. A predictive maintenance program (PdM) was initiated on the SPR during 1993 and 1994. During the development, implementation, and early phases of the PdM program, the program evolved based on lessons learned. The primary areas of involvement and potential improvement in the process are: defining the PdM program based on project needs; obtaining and maintaining support for the program; setting realistic implementation goals and schedules; establishing and justifying manpower levels; developing and involving a project team in the program; developing detailed equipment specifications; identifying training requirements; implementing a phased program; and developing project reporting schemes.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128709813","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513227
S. A. Doyle, J. Dugan, M. Boyd
This paper presents the DREDD (Dependability and Risk Analysis using Decision Diagrams) algorithm which incorporates coverage modeling into a BDD solution of a combinatorial model. The DREDD algorithm takes advantage of the efficiency of the BDD solution approach and the increased accuracy afforded by coverage modeling. BDDs have been used to find exact solutions for extremely large systems, including those with as many as 10/sup 20/ prime implicants. Including coverage in this process will increase the validity of the results, since a more complete model allows for more realistic analysis. The reliability of life critical systems which previously could only be approximated may now be analyzed more accurately.
{"title":"Combinatorial-models and coverage: a binary decision diagram (BDD) approach","authors":"S. A. Doyle, J. Dugan, M. Boyd","doi":"10.1109/RAMS.1995.513227","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513227","url":null,"abstract":"This paper presents the DREDD (Dependability and Risk Analysis using Decision Diagrams) algorithm which incorporates coverage modeling into a BDD solution of a combinatorial model. The DREDD algorithm takes advantage of the efficiency of the BDD solution approach and the increased accuracy afforded by coverage modeling. BDDs have been used to find exact solutions for extremely large systems, including those with as many as 10/sup 20/ prime implicants. Including coverage in this process will increase the validity of the results, since a more complete model allows for more realistic analysis. The reliability of life critical systems which previously could only be approximated may now be analyzed more accurately.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130638832","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513225
T. Jackson, B. Warren
Each reliability requirement extracted from a military standard (MIL-STD-1543, MIL-STD-785, MIL-STD-1629, etc.) must now be justified before a program office can approve its inclusion in a statement of work (SOW). Justification can be based on the criticality of high reliability to achieving program objectives or the lack of substitute commercial standards. With or without standards, the purpose of the reliability program is to assure that reliability engineering is a major contributor to the contractor's systems engineering process. In the case of failure mode and effects criticality analysis (FMECA), an ancillary purpose is to provide proof to the customer (the Air Force in the case of most US Space and launch vehicles) that reliability engineering was in fact included in the systems engineering process. This paper describes guidelines for building a comprehensive reliability engineering database using the failure mode, effects, and criticality analysis record (FMECAR) format.
{"title":"Standardizing the FMECA format: a guideline for Air Force contractors","authors":"T. Jackson, B. Warren","doi":"10.1109/RAMS.1995.513225","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513225","url":null,"abstract":"Each reliability requirement extracted from a military standard (MIL-STD-1543, MIL-STD-785, MIL-STD-1629, etc.) must now be justified before a program office can approve its inclusion in a statement of work (SOW). Justification can be based on the criticality of high reliability to achieving program objectives or the lack of substitute commercial standards. With or without standards, the purpose of the reliability program is to assure that reliability engineering is a major contributor to the contractor's systems engineering process. In the case of failure mode and effects criticality analysis (FMECA), an ancillary purpose is to provide proof to the customer (the Air Force in the case of most US Space and launch vehicles) that reliability engineering was in fact included in the systems engineering process. This paper describes guidelines for building a comprehensive reliability engineering database using the failure mode, effects, and criticality analysis record (FMECAR) format.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122955485","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513236
C. Constantinescu
Development of fault-tolerant computing systems requires accurate reliability assessment techniques. Usually, the reliability measures are functions of component failure rates and fault coverage probabilities. Coverage provides information about the fault and error detection, isolation and system recovery capabilities. This parameter can be estimated by physical or simulated fault injection. One of the most difficult problems the analyst has to deal with, throughout the fault injection process, is the largeness of the fault space. This paper addresses the problem of inferring the coverage probabilities from the information gathered in physical or simulated fault injection experiments. A 3-stage sampling technique is developed for coping with the largeness of the fault space. Statistical experiments are carried out in a three-dimensional fault space which takes into account the inputs applied to the system, fault occurrence times and fault locations.
{"title":"Estimation of the coverage probabilities by 3-stage sampling","authors":"C. Constantinescu","doi":"10.1109/RAMS.1995.513236","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513236","url":null,"abstract":"Development of fault-tolerant computing systems requires accurate reliability assessment techniques. Usually, the reliability measures are functions of component failure rates and fault coverage probabilities. Coverage provides information about the fault and error detection, isolation and system recovery capabilities. This parameter can be estimated by physical or simulated fault injection. One of the most difficult problems the analyst has to deal with, throughout the fault injection process, is the largeness of the fault space. This paper addresses the problem of inferring the coverage probabilities from the information gathered in physical or simulated fault injection experiments. A 3-stage sampling technique is developed for coping with the largeness of the fault space. Statistical experiments are carried out in a three-dimensional fault space which takes into account the inputs applied to the system, fault occurrence times and fault locations.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122689329","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513230
I. Knowles, A. Malhotra, T. Stadterman, Ramesh Munamarty
Technology today is such that the user, or customer, is not able to specify how a product should be developed. The responsibility of developing a reliable product must be placed on the supplier, instead of the customer. This idea should not be new. Military contractors have been saying that the government imposes too many requirements that inhibit innovative design, and often adds cost, with the result being an inferior product. This paper outlines the framework for a next-generation, reliability program standard based on a "code of practice". In this framework, the customer specifies the performance of the product, without stipulating how the supplier must develop, engineer and test the product. The supplier, however, must show that they understand the needs of the customer, can determine the appropriate processes to meet those needs, and can assure the customer that those needs are met. This approach allows the supplier to be flexible and innovative, as long as the customer's needs are met. The Institute of Electrical and Electronics Engineers (IEEE) has initiated an effort to develop a reliability program standard which incorporates these concepts.
{"title":"Framework for a dual-use reliability program standard","authors":"I. Knowles, A. Malhotra, T. Stadterman, Ramesh Munamarty","doi":"10.1109/RAMS.1995.513230","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513230","url":null,"abstract":"Technology today is such that the user, or customer, is not able to specify how a product should be developed. The responsibility of developing a reliable product must be placed on the supplier, instead of the customer. This idea should not be new. Military contractors have been saying that the government imposes too many requirements that inhibit innovative design, and often adds cost, with the result being an inferior product. This paper outlines the framework for a next-generation, reliability program standard based on a \"code of practice\". In this framework, the customer specifies the performance of the product, without stipulating how the supplier must develop, engineer and test the product. The supplier, however, must show that they understand the needs of the customer, can determine the appropriate processes to meet those needs, and can assure the customer that those needs are met. This approach allows the supplier to be flexible and innovative, as long as the customer's needs are met. The Institute of Electrical and Electronics Engineers (IEEE) has initiated an effort to develop a reliability program standard which incorporates these concepts.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"457 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123024031","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513238
J. Evans, P. Lall, R. Bauernschub
The physics-of-failure approach (PoF) to design, reliability modeling, testing and screening of single chip IC packages and multichip modules (MCM), has been developed. The PoF approach is implemented using CADMP-II software. The PoF approach is based on the identification of potential failure mechanisms and failure sites for the product. Failure mechanisms are described by models which characterize the physics of degradation processes leading to failure at each potential failure site. The loads at each failure site are obtained as a function of environmental and operation conditions. The approach preactively incorporates reliability in the design process by establishing a scientific basis for evaluation of new materials, structures, and technologies, through design of tests, screens, safety factors, and acceleration transforms, based on the knowledge of failure mechanisms and modes.
{"title":"A framework for reliability modeling of electronics","authors":"J. Evans, P. Lall, R. Bauernschub","doi":"10.1109/RAMS.1995.513238","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513238","url":null,"abstract":"The physics-of-failure approach (PoF) to design, reliability modeling, testing and screening of single chip IC packages and multichip modules (MCM), has been developed. The PoF approach is implemented using CADMP-II software. The PoF approach is based on the identification of potential failure mechanisms and failure sites for the product. Failure mechanisms are described by models which characterize the physics of degradation processes leading to failure at each potential failure site. The loads at each failure site are obtained as a function of environmental and operation conditions. The approach preactively incorporates reliability in the design process by establishing a scientific basis for evaluation of new materials, structures, and technologies, through design of tests, screens, safety factors, and acceleration transforms, based on the knowledge of failure mechanisms and modes.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131187575","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513257
D. Sherwin
Automatic trips and warning instruments (TWI) protect important machines by shutting them down or warning the operators of impending serious failure. They are subject to hidden faults which must be discovered and corrected at frequent inspections, and spurious trips when the machine is stopped unnecessarily because of a fault in the TWI spurious trips may also be reduced by inspections. A Markov model is used to optimize the inspection rate with respect to costs on the assumption that inspection is a Poisson event. This simplifies the mathematics compared to a model with periodic inspections and is often just as close to the truth. An example is given involving gas-turbines in the off-shore oil industry. An extension of the model covers the case of 2-out-of-3 voting systems which are increasingly used to reduce the risks of both types of TWI failure. The optimizations are usually rather flat around the optimum, and inspections often have to fit in with operational needs, so approximate methods such as this are potentially very useful as the example illustrates.
{"title":"An inspection model for automatic trips and warning instruments","authors":"D. Sherwin","doi":"10.1109/RAMS.1995.513257","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513257","url":null,"abstract":"Automatic trips and warning instruments (TWI) protect important machines by shutting them down or warning the operators of impending serious failure. They are subject to hidden faults which must be discovered and corrected at frequent inspections, and spurious trips when the machine is stopped unnecessarily because of a fault in the TWI spurious trips may also be reduced by inspections. A Markov model is used to optimize the inspection rate with respect to costs on the assumption that inspection is a Poisson event. This simplifies the mathematics compared to a model with periodic inspections and is often just as close to the truth. An example is given involving gas-turbines in the off-shore oil industry. An extension of the model covers the case of 2-out-of-3 voting systems which are increasingly used to reduce the risks of both types of TWI failure. The optimizations are usually rather flat around the optimum, and inspections often have to fit in with operational needs, so approximate methods such as this are potentially very useful as the example illustrates.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115907253","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513293
P. Dersin, J. Durand
Service quality is influenced not only by intrinsic reliability and maintainability but also by logistical factors such as: the number of operations reserves of spare trains; the number of repair facilities; fleet size; average recovery times after perturbations; and spare parts. Operators are looking for service quality commitments from manufacturers. However, only intrinsic reliability and maintainability, and to some extent, service reliability, are determined by the manufacturer's design. This paper addresses quantitatively the dependence of service quality on intrinsic reliability and maintainability, and logistic variables. Analytical models, based on Markov chains, are used to derive the corresponding relationships. Sensitivity analyses can then be performed. Tradeoffs can be assessed quantitatively between several solutions for achieving a given service quality target at different costs. On the basis of such a tradeoff analysis. The effort toward a higher service quality can be guided in a life-cycle cost perspective. Also, reliability and maintainability apportionments can be performed which are derived from the service quality objective. Logistic parameters are seen to play a key part. Accordingly, the manufacturer which does not control maintenance may find it inappropriate to commit to a service quality level, but may commit, instead, to reliability and maintainability levels that, under precise assumptions on the logistics, result in the desired service quality.
{"title":"Mass-transit system service quality: tradeoff analysis on reliability, maintainability and logistics","authors":"P. Dersin, J. Durand","doi":"10.1109/RAMS.1995.513293","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513293","url":null,"abstract":"Service quality is influenced not only by intrinsic reliability and maintainability but also by logistical factors such as: the number of operations reserves of spare trains; the number of repair facilities; fleet size; average recovery times after perturbations; and spare parts. Operators are looking for service quality commitments from manufacturers. However, only intrinsic reliability and maintainability, and to some extent, service reliability, are determined by the manufacturer's design. This paper addresses quantitatively the dependence of service quality on intrinsic reliability and maintainability, and logistic variables. Analytical models, based on Markov chains, are used to derive the corresponding relationships. Sensitivity analyses can then be performed. Tradeoffs can be assessed quantitatively between several solutions for achieving a given service quality target at different costs. On the basis of such a tradeoff analysis. The effort toward a higher service quality can be guided in a life-cycle cost perspective. Also, reliability and maintainability apportionments can be performed which are derived from the service quality objective. Logistic parameters are seen to play a key part. Accordingly, the manufacturer which does not control maintenance may find it inappropriate to commit to a service quality level, but may commit, instead, to reliability and maintainability levels that, under precise assumptions on the logistics, result in the desired service quality.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115462423","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 : 1995-01-16DOI: 10.1109/RAMS.1995.513281
A. Chandra, G. Ahrens, M. Kanthanathan, J. Grzinich
We show an empirically driven process to validate the availability models of RISC System/6000 workstations. The empirical data is obtained by tracking RISC System/6000 workstations in the field. The tracking data is obtained by using customer surveys and by using an availability measurement tool installed on selected running systems. We model several types of RISC System/6000 workstations using the SAVE tool. Care is taken to include all classes of systems. The workstations modeled include representatives from the desktop, deskside, and rack families. We explain the key principle of the "representative field model." For each type of workstation modeled, availability data for validation is extracted from the customer survey database or the availability measurement database. The validation data is used to identify and eliminate model errors. The identification and elimination of modeling errors involves sensitivity analysis. The validation of the availability measures of several RISC System/6000 workstations using both survey and measurement data confirms the accuracy of our modeling process and gives us the confidence to utilize the availability models in our development and marketing processes. Also, this enables us to generate accurate availability measures in our future availability modeling efforts.
{"title":"Empirical validation of availability models for the RISC System/6000 workstation using survey and measurement data","authors":"A. Chandra, G. Ahrens, M. Kanthanathan, J. Grzinich","doi":"10.1109/RAMS.1995.513281","DOIUrl":"https://doi.org/10.1109/RAMS.1995.513281","url":null,"abstract":"We show an empirically driven process to validate the availability models of RISC System/6000 workstations. The empirical data is obtained by tracking RISC System/6000 workstations in the field. The tracking data is obtained by using customer surveys and by using an availability measurement tool installed on selected running systems. We model several types of RISC System/6000 workstations using the SAVE tool. Care is taken to include all classes of systems. The workstations modeled include representatives from the desktop, deskside, and rack families. We explain the key principle of the \"representative field model.\" For each type of workstation modeled, availability data for validation is extracted from the customer survey database or the availability measurement database. The validation data is used to identify and eliminate model errors. The identification and elimination of modeling errors involves sensitivity analysis. The validation of the availability measures of several RISC System/6000 workstations using both survey and measurement data confirms the accuracy of our modeling process and gives us the confidence to utilize the availability models in our development and marketing processes. Also, this enables us to generate accurate availability measures in our future availability modeling efforts.","PeriodicalId":143102,"journal":{"name":"Annual Reliability and Maintainability Symposium 1995 Proceedings","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124747954","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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