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The computer program listing for the reliability block diagram computation program described in Reliability Computation From Reliability Block Diagrams is given. The program is written in FORTRAN 4 and is currently running on a Univac 1108. Each subroutine contains a description of its function.
Computer program computes system reliability for very general class of reliability block diagrams. Four factors are considered in calculating probability of system success: active block redundancy, standby block redundancy, partial redundancy, and presence of equivalent blocks in the diagram.
A method and a computer program are presented to calculate probability of system success from an arbitrary reliability block diagram. The class of reliability block diagrams that can be handled include any active/standby combination of redundancy, and the computations include the effects of dormancy and switching in any standby redundancy. The mechanics of the program are based on an extension of the probability tree method of computing system probabilities.
In order to perform public risk analyses for vehicles containing Flight Termination Systems (FTS), it is necessary for the analyst to know the reliability of each of the components of the FTS. These systems are typically divided into two segments; a transmitter system and associated equipment, typically in a ground station or on a support aircraft, and a receiver system and associated equipment on the target vehicle. This analysis attempts to analyze the reliability of the NASA DFRC flight termination system ground transmitter segment for use in the larger risk analysis and to compare the results against two established Department of Defense availability standards for such equipment.
Field Programmable Gate Arrays (FPGAs) integrated circuits (IC) are one of the key electronic components in today's sophisticated launch and space vehicle complex avionic systems, largely due to their superb reprogrammable and reconfigurable capabilities combined with relatively low non-recurring engineering costs (NRE) and short design cycle. Consequently, FPGAs are prevalent ICs in communication protocols and control signal commands. This paper will identify reliability concerns and high level guidelines to estimate FPGA total failure rates in a launch vehicle application. The paper will discuss hardware, hardware description language, and radiation induced failures. The hardware contribution of the approach accounts for physical failures of the IC. The hardware description language portion will discuss the high level FPGA programming languages and software/code reliability growth. The radiation portion will discuss FPGA susceptibility to space environment radiation.
No abstract available
This paper presents Helios Critical Design Review Reliability form October 16-20, 1972. The topics include: 1) Reliability Requirement; 2) Reliability Apportionment; 3) Failure Rates; 4) Reliability Assessment; 5) Reliability Block Diagram; and 5) Reliability Information Sheet.
The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.
The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.
The Space Shuttle Orbiter is the only space reentry vehicle in which the crew is seated upright. This position presents some physiological effects requiring countermeasures to prevent a crewmember from becoming incapacitated. This also introduces a potential need for automated vehicle landing capability. Autoland is a primary procedure that was identified as a requirement for landing following and extended duration orbiter mission. This report documents the results of the reliability analysis performed on the hardware required for an automated landing. A reliability block diagram was used to evaluate system reliability. The analysis considers the manual and automated landing modes currently available on the Orbiter. (Autoland is presently a backup system only.) Results of this study indicate a +/- 36 percent probability of successfully extending a nominal mission to 30 days. Enough variations were evaluated to verify that the reliability could be altered with missions planning and procedures. If the crew is modeled as being fully capable after 30 days, the probability of a successful manual landing is comparable to that of Autoland because much of the hardware is used for both manual and automated landing modes. The analysis indicates that the reliability for the manual mode is limited by the hardware and depends greatly on crew capability. Crew capability for a successful landing after 30 days has not been determined yet.
A preliminary failure mode, failure effect, and criticality analysis of the major subsystems of nuclear electric propulsion is presented. Simplified reliability block diagrams are also given. A computer program was used to calculate the reliability of the heat rejection subsystem.
Computer program to calculate probability of system success from arbitrary reliability block diagram using IBM 1620
A user's manual describing an interactive, menu-driven, personal computer based Monte Carlo reliability, availability, and maintainability simulation program called event time availability reliability (ETARA) is discussed. Given a reliability block diagram representation of a system, ETARA simulates the behavior of the system over a specified period of time using Monte Carlo methods to generate block failure and repair intervals as a function of exponential and/or Weibull distributions. Availability parameters such as equivalent availability, state availability (percentage of time as a particular output state capability), continuous state duration and number of state occurrences can be calculated. Initial spares allotment and spares replenishment on a resupply cycle can be simulated. The number of block failures are tabulated both individually and by block type, as well as total downtime, repair time, and time waiting for spares. Also, maintenance man-hours per year and system reliability, with or without repair, at or above a particular output capability can be calculated over a cumulative period of time or at specific points in time.
A National Aeronautics and Space Administration (NASA) supported Reliability, Maintainability, and Availability (RMA) analysis team developed a unique RMA analysis methodology using cut set and importance measure analysis in order to comparison model proposed avionics computing architectures. In this paper we will present this efficient application of the RMA analysis methodology for importance measures that includes Reliability Block Diagram (RED) Analysis, Comparison modeling, Cut Set Analysis, and Importance Measure Analysis. We will also demonstrate that integrating RMA early in the system design process as a key to success by providing a fundamental decision metric supporting design selection. The RMA analysis methodology presented in this paper and applied to the avionics architectures enhances the usual way of predicting the need for redundancy based on failure rates or subject matter expert opinion. Using the REDs and the minimal cut sets, along with the Fussell-Vesely (FV) factors, importance measures are calculated for each functional element in the architectures. This paper presents an application of the FV importance measures and presents an improved methodology for using importance measures in success space (instead of failure space) to compare architectures. These importance measures are used to determine which functional element would be most likely to cause a system failure, thus, quickly identifying the path to increase the overall system reliability by either procuring more reliable functional elements or adding redundancy. This application of the RMA analysis methodology, using RBD analysis, cut set analysis, and the importance measure analysis, allows the avionics design team to better understand and compare the vulnerabilities in each of the architectures, enabling them to address the deficiencies in the design architectures more efficiently, while balancing the need to design for optimum weight and space allocations.
The computer program listing for the MAIN program and those subroutines unique to the fault tree analysis are described. Some subroutines are used for analyzing the reliability block diagram. The program is written in FORTRAN 5 and is running on a UNIVAC 1108.
Control elements such as sensors, momentum exchange devices, and thrusters are described which can be used to define space replaceable units (SRU), in accordance with attitude control, guidance, and navigation performance requirements selected for NASA space serviceable mission spacecraft. A number of SRU's are developed, and their reliability block diagrams are presented. An SRU assignment is given in order to define a set of feasible space serviceable spacecraft for the missions of interest.
The Reliability and Maintainability Assessment Tool is a stochastic, event-oriented simulation model that has been developed to analyze the functional reliability, availability, and maintainability characteristics of the Space Station Freedom. This tool simulates failures and performs corrective and preventive maintenance tasks, utilizing user-specified maintenance resources, including crewmembers and/or robotics, and accommodates the growth of the station. The model dynamically interfaces with minimal cut sets derived from reliability block diagrams to assess functional status and to determine queuing priorities.
The technical personnel in the SEMA office are working to provide the highest degree of value-added activities to their support of the NASA Langley Research Center mission. Management perceives that reliability analysis tools and an understanding of a comprehensive systems approach to reliability will be a foundation of this change process. Since the office is involved in a broad range of activities supporting space mission projects and operating activities (such as wind tunnels and facilities), it was not clear what reliability tools the office should be familiar with and how these tools could serve as a flexible knowledge base for organizational growth. Interviews and discussions with the office personnel (both technicians and engineers) revealed that job responsibilities ranged from incoming inspection to component or system analysis to safety and risk. It was apparent that a broad base in applied probability and reliability along with tools for practical application was required by the office. A series of ten class sessions with a duration of two hours each was organized and scheduled. Hand-out materials were developed and practical examples based on the type of work performed by the office personnel were included. Topics covered were: Reliability Systems - a broad system oriented approach to reliability; Probability Distributions - discrete and continuous distributions; Sampling and Confidence Intervals - random sampling and sampling plans; Data Analysis and Estimation - Model selection and parameter estimates; and Reliability Tools - block diagrams, fault trees, event trees, FMEA. In the future, this information will be used to review and assess existing equipment and processes from a reliability system perspective. An analysis of incoming materials sampling plans was also completed. This study looked at the issues associated with Mil Std 105 and changes for a zero defect acceptance sampling plan.