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A computational algorithm for reliability bounds in probabilistic design
588
World Abstracts on Microelectronics and Reliability
Reliability growth measurement applied to ESS. B. C. SPRADLIN. Proc. a. Reliab. Maintainab. Symp., 97 (1986). Environmental stress screening (ESS) has become a useful means for detecting and eliminating latent defects in equipment prior to field usage. However, its application in the form of random vibration and temperature cycling (as described in the 1979 Navy Report NAVMATP-9492) is relatively new. Moreover, when applied to new products, certain questions arise, answers to which are needed for planning purposes and progress determination. For example, what number of failures per equipment should be expected? How do we measure our progress? A technique to aid in answering such questions has been applied to an electromechanical equipment with very good results. The technique, based on a modification of Duane's reliability growth curves, utilized initial testing results to develop a curve of expected failure rate as a function of cumulative numbers of equipments undergoing test. The curve, a decreasing exponential, aided testing effort planning, and provided a useful measure of progress in decreasing the failure rate for the equipment. This paper describes how the curve of expected failure rate was developed, and presents the subsequent data obtained for over a year's equipment production. With one exception, caused by a problem component, the data followed the curve extremely close. If further applications of the technique prove it's validity, it could be a very useful tool for planning efforts and monitoring improvement in equipment as shown by environmental stress screening results.
Multiple-stress
assembly-level
stress screening. JOEL A.
NACHLAS, LORE E. SEWARD and BLAIR A. BINNEY. Proc. a. Reliab. Maintainab. Syrup., 40 (1986). A general cost model for use in selecting a stress regimen for a multiple-stress assembly-level stress screen is developed. The model represents the balance between the benefits of improved early-life product field performance and the costs of applying a stress screen to obtain those benefits. The model is general in that it can be used to represent any series assembly and any set of stress variables. It can also be simplified for use with a single component or a single stress variable. The model takes the form of an unconstrained non-convex nonlinear program. It can be solved by any of several methods. An example formulation is described here and solution of the example by the generalized reduced gradient method is demonstrated
Evaluation of large fault-trees with repeated events using an efficient bottom-up algorithm. KARL STECHER. IEEE Trans. Reliab. R-35, 51 (1986). In current fault-tree analysis of
systems, the usual algorithms for evaluation of fault-trees with repeated events apply the method of minimal cuts. Since the number of minimal cuts increases exponentially with the number of system components, truncation as well as optimization techniques have to be performed for the evaluation of large fault-trees. This paper presents an algorithm which combines the bottom-up algorithm for fault-trees without repeated events with the bottom-up algorithm for establishing the structure function of a fault-tree with repeated events. It allows convenient modeling and evaluation of large fault-trees with repeated events and it computes the exact reliability characteristics, such as steady-state and time-dependent system unavailability and failure rate for repairable and nonrepairable systems. This algorithm has been implemented by a computer program and has been in use at the Power Engineering and Automation Group of Siemens AG. The program includes many features for the description and modular structuring of fault-trees, e.g. (I) definition of fault-tree modules, which can also be declared as repeated transmission trees; (2) a subtree can be used several times as a transmission tree, representing
many modules of the system; (3) repeated events with respect to a subtree level.
A computational algorithm for reliability bounds in probabilisfic design. JIN WON PARK and GORDON M. CLARK. IEEE Trans. Reliab. R-35, 30 (1986). Kapur formulated quadratic programming problems for determining bounds on the design reliability, given some bounds on the probabilities of the stress and strength random variables. We modify Kapur's formulation to improve its accuracy, and present a solution to the resulting quadratic programming problems that can be evaluated manually.
Zero-defect
software: the elusive goal. MARGARET H. HAMILTON. IEEE Spectrum, 48 (March 1986). It is theoretically possible but difficult to achieve; logic and interface errors are most common, but errors in user intent may also OCCUr.
Reverse tailoring for realistic reliability tests. HENRY CARUSO. Proc. a. Reliab. Maintainab. Syrup., 397 (1986). Reverse
tailoring is proposed as an analytical process whereby the environmental engineering specialist can evaluate the validity of specified environmental design and test criteria. Detailed examples are presented for traditionally specified high- and low-temperature values for airborne electronics. Mission-use considerations and basic physics, combined with published literature and interviews with the equipment operators, can he used to establish realistic environmental criteria in the absence of specific measured data.
Specifying operational availability. HERBERTDAGEN. Proc. a. Reliab. Maintainab. Symp., 145 (1986). There are three methodological aspects of operational availability: specifying, predicting and testing. Over the years, much has been said and written about the predicting and testing aspects of operational availability, although this is not to imply that the last word has been said on either of these two aspects. However, there has been very little said, in the literature anyway, about how one goes about logically specifying operational availability, other than that the requirement should somehow be related to the mission use profile of the system for which the specified value is needed. Operational availability is a measure of a system's readiness to perform a function and is influenced by the effects of reliability, maintainability, and supportability for a defined mission use profile. Usually, system analysis attempts to maximize the availability for the least life cycle costs, but without knowing what the acceptable availability value should be in relation to the mission use profile of the system. However, once the operational availability is specified, cost trade-offs between reliability, maintainability and supportability can be made to ascertain the most affordable system(s) that meets the requirement. In specifying operational availability, the first decision that must be made is to identify the mission use profile(s), including the timeframe. The next decision is to choose which approach to use in order to generate a quantifiable value for operational availability. Here, one might use intuition, historical data or analysis of the mission use profile. This paper describes a simple procedure, used by the Navy on at least two systems, which logically examines the mission use profile to allow specification of an operational availability value before the system is configured.
Detection and ranking of culprit variables. JEAN MIRRA, FRANK McNOLTY and WILLIAM SHERWOOD.Proc. a. Reliab. Maintainab. Syrup., 232 (1986). Extremely large-scale multivariate reliability analyses require specialized methodology, oriented toward computer-man-hour parsimony, stability and quick response time. Techniques are provided for detecting and ranking culprit variables in a real-world data
World Abstracts on Microelectronics and Reliability
Reliability growth measurement applied to ESS. B. C. SPRADLIN. Proc. a. Reliab. Maintainab. Symp., 97 (1986). Environmental stress screening (ESS) has become a useful means for detecting and eliminating latent defects in equipment prior to field usage. However, its application in the form of random vibration and temperature cycling (as described in the 1979 Navy Report NAVMATP-9492) is relatively new. Moreover, when applied to new products, certain questions arise, answers to which are needed for planning purposes and progress determination. For example, what number of failures per equipment should be expected? How do we measure our progress? A technique to aid in answering such questions has been applied to an electromechanical equipment with very good results. The technique, based on a modification of Duane's reliability growth curves, utilized initial testing results to develop a curve of expected failure rate as a function of cumulative numbers of equipments undergoing test. The curve, a decreasing exponential, aided testing effort planning, and provided a useful measure of progress in decreasing the failure rate for the equipment. This paper describes how the curve of expected failure rate was developed, and presents the subsequent data obtained for over a year's equipment production. With one exception, caused by a problem component, the data followed the curve extremely close. If further applications of the technique prove it's validity, it could be a very useful tool for planning efforts and monitoring improvement in equipment as shown by environmental stress screening results.
Multiple-stress
assembly-level
stress screening. JOEL A.
NACHLAS, LORE E. SEWARD and BLAIR A. BINNEY. Proc. a. Reliab. Maintainab. Syrup., 40 (1986). A general cost model for use in selecting a stress regimen for a multiple-stress assembly-level stress screen is developed. The model represents the balance between the benefits of improved early-life product field performance and the costs of applying a stress screen to obtain those benefits. The model is general in that it can be used to represent any series assembly and any set of stress variables. It can also be simplified for use with a single component or a single stress variable. The model takes the form of an unconstrained non-convex nonlinear program. It can be solved by any of several methods. An example formulation is described here and solution of the example by the generalized reduced gradient method is demonstrated
Evaluation of large fault-trees with repeated events using an efficient bottom-up algorithm. KARL STECHER. IEEE Trans. Reliab. R-35, 51 (1986). In current fault-tree analysis of
systems, the usual algorithms for evaluation of fault-trees with repeated events apply the method of minimal cuts. Since the number of minimal cuts increases exponentially with the number of system components, truncation as well as optimization techniques have to be performed for the evaluation of large fault-trees. This paper presents an algorithm which combines the bottom-up algorithm for fault-trees without repeated events with the bottom-up algorithm for establishing the structure function of a fault-tree with repeated events. It allows convenient modeling and evaluation of large fault-trees with repeated events and it computes the exact reliability characteristics, such as steady-state and time-dependent system unavailability and failure rate for repairable and nonrepairable systems. This algorithm has been implemented by a computer program and has been in use at the Power Engineering and Automation Group of Siemens AG. The program includes many features for the description and modular structuring of fault-trees, e.g. (I) definition of fault-tree modules, which can also be declared as repeated transmission trees; (2) a subtree can be used several times as a transmission tree, representing
many modules of the system; (3) repeated events with respect to a subtree level.
A computational algorithm for reliability bounds in probabilisfic design. JIN WON PARK and GORDON M. CLARK. IEEE Trans. Reliab. R-35, 30 (1986). Kapur formulated quadratic programming problems for determining bounds on the design reliability, given some bounds on the probabilities of the stress and strength random variables. We modify Kapur's formulation to improve its accuracy, and present a solution to the resulting quadratic programming problems that can be evaluated manually.
Zero-defect
software: the elusive goal. MARGARET H. HAMILTON. IEEE Spectrum, 48 (March 1986). It is theoretically possible but difficult to achieve; logic and interface errors are most common, but errors in user intent may also OCCUr.
Reverse tailoring for realistic reliability tests. HENRY CARUSO. Proc. a. Reliab. Maintainab. Syrup., 397 (1986). Reverse
tailoring is proposed as an analytical process whereby the environmental engineering specialist can evaluate the validity of specified environmental design and test criteria. Detailed examples are presented for traditionally specified high- and low-temperature values for airborne electronics. Mission-use considerations and basic physics, combined with published literature and interviews with the equipment operators, can he used to establish realistic environmental criteria in the absence of specific measured data.
Specifying operational availability. HERBERTDAGEN. Proc. a. Reliab. Maintainab. Symp., 145 (1986). There are three methodological aspects of operational availability: specifying, predicting and testing. Over the years, much has been said and written about the predicting and testing aspects of operational availability, although this is not to imply that the last word has been said on either of these two aspects. However, there has been very little said, in the literature anyway, about how one goes about logically specifying operational availability, other than that the requirement should somehow be related to the mission use profile of the system for which the specified value is needed. Operational availability is a measure of a system's readiness to perform a function and is influenced by the effects of reliability, maintainability, and supportability for a defined mission use profile. Usually, system analysis attempts to maximize the availability for the least life cycle costs, but without knowing what the acceptable availability value should be in relation to the mission use profile of the system. However, once the operational availability is specified, cost trade-offs between reliability, maintainability and supportability can be made to ascertain the most affordable system(s) that meets the requirement. In specifying operational availability, the first decision that must be made is to identify the mission use profile(s), including the timeframe. The next decision is to choose which approach to use in order to generate a quantifiable value for operational availability. Here, one might use intuition, historical data or analysis of the mission use profile. This paper describes a simple procedure, used by the Navy on at least two systems, which logically examines the mission use profile to allow specification of an operational availability value before the system is configured.
Detection and ranking of culprit variables. JEAN MIRRA, FRANK McNOLTY and WILLIAM SHERWOOD.Proc. a. Reliab. Maintainab. Syrup., 232 (1986). Extremely large-scale multivariate reliability analyses require specialized methodology, oriented toward computer-man-hour parsimony, stability and quick response time. Techniques are provided for detecting and ranking culprit variables in a real-world data