DOCSLIB.ORG

NASA Activities in Risk Assessment

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
NASA Activities in Risk Assessment NASANASA ActivitiesActivities inin RiskRisk AssessmentAssessment NASANASA ProjectProject ManagementManagement ConferenceConference MarchMarch 30-31,30-31, 20042004 Michael G. Stamatelatos, Ph.D.,Director Safety and Assurance Requirements Division Office of Safety and Mission Assurance NASA Headquarters 1 NASA is a Pioneer and a Leader in Space; Therefore Its Business Is Inherently Risky International Space Station Safe assembly and operation Space Transportation Space Shuttle Orbital Space Plane 2 Our Goal z Improve risk awareness in the Agency ¾ Conduct PRA training for line and project managers and for personnel z Develop a corps of in-house PRA experts z Transition PRA from a curiosity object to baseline method for integrated system safety, reliability and risk assessment z Adopt organization-wide risk informed culture ¾ PRA to become a way of life for safety and technical performance improvement and for cost reduction ¾ Implement risk-informed management process 3 Probabilistic Risk Assessment (PRA) Answers Three Basic Questions Risk is a set of triplets that answer the questions: 1) What can go wrong? (accident scenarios) 2) How likely is it? (probabilities) 3) What are the consequences? (adverse effects) Kaplan & Garrick, Risk Analysis, 1981 Event Event Sequence Sequence Frequency Modeling Evaluation 2. How frequently does it happen? (Scenario frequency quantification) Event Initiating Sequence Risk Event PRA Insights Logic Integration Selection Development 1. What can go wrong? Risk statement Decision Support (Definition of scenarios) 3. What are the consequences? (Scenario consequence quantification) Consequence Modeling PRA is generally used for low-probability and high- consequence events 4 Relationship Between Risk Management and Probabilistic Risk Assessment (PRA) Continuous Risk Management Method Technique Application QualitativeQualitative FMEA. RiskRisk FMEA. MLD, AssessmenAssessmentt MLD, ESD,ESD, Technical ETA, Technical ETA, RiskRisk FTA,FTA, RBDRBD and/or ProbabilisticProbabilistic and/or Risk Risk Program Assessment ActuActuarial/arial/ Program Assessment Risk StatisticalStatistical Risk AnalyAnalysesses Legend: Decision Decision FMEA - Failure Modes & Effects Analysis Analysis Analysis MLD - Master Logic Diagram ManagementManagement ESD - Event Sequence Diagram SySystemstem ETA - Event Tree Analysis FTA - Fault Tree Analysis RBD - Reliability Block Diagram 5 NASA Risk Management and Assessment Requirements • NPG 7120.5A, NASA Program and Project Management Processes and Requirements ¾ The program or project manager shall apply risk management principles as a decision-making tool which enables programmatic and technical success. ¾ Program and project decisions shall be made on the basis of an orderly risk management effort. ¾ Risk management includes identification, assessment, mitigation, and disposition of risk throughout the PAPAC (Provide Aerospace Products And Capabilities) process. • NPG 8000.4, Risk Management Procedures and Guidelines ¾ Provides additional information for applying risk management as required by NPG 7120.5A. • NPG 8705.x (draft) PRA Application Procedures and Guidelines ¾ Provides guidelines on how to apply PRA to NASA’s diversified programs and projects 6 How Does PRA Help Safety? Provides a basis for risk reduction through: 1. Accident/Mishap Prevention (best) 2. Accident/Mishap Consequence Mitigation Adverse Event in a Sequence Prevention Mitigation 7 The Concept of an Accident Scenario PIVOTAL EVENTS Pivotal Pivotal End State IE Event 1 Event n Detrimental The perturbation Mitigative consequence of Aggrevative interest (Quantity of intereset to decision-maker) Risk Scenario is a string of events that (if they occur) will lead to an undesired end state. 8 Exact vs. Uncertain Probabilities Uncertainty distribution of probability values Exactly known probability ability ability b value b Pro Pro A narrower range means a more precise knowledge of the distribution, or less uncertainty 9 Quantification of Uncertainty Probability density function, e.g., probability of LOCV Uncertainty Distribution: P(x) is the probability (or xth percentile ρ(x) confidence) that the result value is x P(x) median is the 50th percentile is area under 5% x 50% 95% curve between Median 0 and x Uncertainty Range: Uncertainty range 5th percentile 95th percentile (spread) from the 5th to the 95th percentile Uncertainty (confidence) range 10 Event- and Fault-Tree Scenario Modeling No damage to No damage to Hydrazine leaks Leak detected Leak isolated flight critical scientific End state Leak not detected avionics equipment IE LD LI A S OK Loss of science Loss of Spacecraft Presure Presure Controller fails transducer 1 transducer 2 OK fails fails Loss of science CN P1 P2 common cause Loss of failure of P. Spacecraft transducers OK PP distribution Loss of science Loss of Spacecraft Fault tree Event tree 11 PRA Methodology Synopsis Inputs to Decision Making Process Master Logic Diagram (Hierarchical Logic) Event Sequence Diagram (Logic) IE End State: ES1 A B End State: OK EnEndd S Stattate:e: ES2 ES2 End State: ES2 C D E End State: ES1 End State: ES2 LING DE C MO Event Tree (Inductive Logic) Fault Tree (Logic) One to Many Mapping of an ET-defined Scenario I End Not A IE A B C D E NEW STRUCTURE State LOG Logic Gate 1: OK Basic Event Internal initiating events One of these events External initiating events 2: ES1 Hardware components AND 3: ES2 Human error 4: ES2 Software error one or more Common cause of these 5: ES2 elementary Environmental conditions events 6: ES2 Other Link to another fault tree Probabilistic Treatment of Basic Events Model Integration and Quantification of Risk Scenarios Risk Results and Insights 30 50 60 25 50 40 End State: ES2 Integration and quantification of 20 40 30 100 logic structures (ETs and FTs) 15 IC 30 Displaying the results in tabular and graphical forms 10 20 80 and propagation of epistemic 20 uncertainties to obtain Ranking of risk scenarios 10 5 10 End State: ES1 60 ST 0.02 0.04 0.06 0.08 Ranking of individual events (e.g., hardware failure, I 0.01 0.02 0.03 0.04 0.02 0.04 0.06 0.08 minimal cutsets (risk 40 human errors, etc.) scenarios in terms of Examples (from left to right): 20 basic events) Insights into how various systems interact Probability that the hardware x fails when needed likelihood of risk Tabulation of all the assumptions ABIL Probability that the crew fail to perform a task 0.01 0.02 0.03 0.04 0.05 scenarios Identification of key parameters that greatly B Probability that there would be a windy condition at the time of landing uncertainty in the likelihood estimates influence the results The uncertainty in occurrence of an event is Presenting results of sensitivity studies characterized by a probability distribution PRO 12 What Decision Types Can PRA Support? z Safety improvement in design, operation, maintenance and upgrade (throughout life cycle); z Mission success enhancement; z Performance improvement; and z Cost reduction for design, operation and maintenance For all these areas of application, PRA can help: z Identify leading risk contributors and their relative values z Indicate priorities for resource allocation z Optimize results for given resource availability 13 Areas of PRA Application at NASA z In Design and Conceptual Design (e.g., Crew Exploration Vehicle, Mars missions, Project Prometheus) z For Upgrades (Space Shuttle) z For Development/construction/assembly (e.g., International Space Station) z When there are requirements for Safety Compliance (e.g., nuclear missions like Mars ’03; Project Prometheus, Mars Sample Return) 14 NASA Procedural Requirement NPR 8705 (Draft) CONSEQUENCE NASA PROGRAM/PROJECT CRITERIA / SPECIFICS PRA SCOPE CATEGORY (Classes and/or Examples) Planetary Protection Program Mars Sample Return Missions F Requirement White House Approval Nuclear Payloads Public Safety F (PD/NSC-25) (e.g., Cassini, Ulysses, Mars 2003) Human Safety and Space Missions with Flight Launch Vehicles F Health Termination Systems International Space Station F Human Space Flight Space Shuttle F Orbital Space Plane/Space Launch Initiative F High Strategic Importance Mars Program F Launch Window High Schedule Criticality F (e.g., planetary missions) Mission Success Earth Science Missions L/S (for non-human (e.g., EOS, QUICKSCAT) rated missions) Space Science Missions All Other Missions L/S (e.g., SIM, HESSI) Technology Demonstration/Validation (e.g., L/S EO-1, Deep Space 1) F = Full scope; L/S = Limited or Simplified PRA Scope Legend: F = Full scope; L = Limited scope; S = Simplified PRA 15 NASA Special PRA Methodology Needs z Broad range of programs: Conceptual non-human rated science projects; Multi-stage design and construction of the International Space Station; Upgrades of the Space Shuttle z Risk initiators that vary drastically with type of program z Unique design and operating environments (e.g., microgravity effects on equipment and humans) z Multi-phase approach in some scenario developments z Unique external events (e.g., micro-meteoroids and orbital debris) z Unique types of adverse consequences (e.g., fatigue and illness in space) and associated databases z Different quantitative methods for human reliability (e.g., astronauts vs. other operating personnel) z Quantitative methods for software reliability 16 Space Shuttle Probabilistic Risk Assessment 17 STS Nominal Mission Profile ASCENT completes ORBIT completes APU Shutdown TAL TIG-5 t ~ 150kft) SSME start ENTRY completes APU start 18 Current Shuttle PRA Results for LOCV (provisional) 1/10025 median = 1 in 123 y t i s n e on i D mean = 1 in 76 t y t i l i 5th percentile = 1 in 617 Func ab b o r 95th percentile = 1 in 23 P 1/250 0.1/00500 1/0.10001 0.1/0250 1/0.3303 1/0.2504 1/0.2005 truncated Number of Missions 19 Summary of Shuttle PRA Historical Results 1993 PRA 1988 PRA update the First PRA 2003 PRA 1998 PRA Galileo study conducted on Integrated Unpublished 1995 PRA results to reflect the Space PRA with all analysis using First major the current Shuttle for 0.1 elements. QRAS. No study of (April 1993) test 1996 PRA ascent only, 18 Orbiter Integration of 1997 PRA Shuttle PRA.
Load more

Recommended publications
  • A Zonal Safety Analysis Methodology for Preliminary Aircraft Systems and Structural Design
    A Zonal Safety Analysis Methodology for Preliminary Aircraft Systems and Structural Design Chen, Z. and Fielding, J. P. School of Aerospace, Transport and Manufacturing, Cranfield University ABSTRACT Zonal Safety Analysis (ZSA) is a major part of the civil aircraft safety assessment process described in Aerospace Recommended Practice 4761 (ARP4761). It considers safety effects that systems/items installed in the same zone (i.e. a defined area within the aircraft body) may have on each other. Although the ZSA may be conducted at any design stage, it would be most cost-effective to do it during preliminary design, due to the greater opportunity for influence on system and structural designs and architecture. The existing ZSA methodology of ARP4761 was analysed but it was found to be more suitable for detail design rather than preliminary design. The authors therefore developed a methodology that would be more suitable for preliminary design and named it the Preliminary Zonal Safety Analysis (PZSA). This new methodology was verified by means of the use of a case-study, based on the NASA N3-X project. Several lessons were learnt from the case study, leading to refinement of the proposed method. These lessons included focusing on the positional layout of major components for the zonal safety inspection, and using the Functional Hazard Analysis (FHA)/Fault Tree Analysis (FTA) to identify system external failure modes. The resulting PZSA needs further refinement, but should prove to be a useful design tool for the preliminary design process. _____________________________________ INTRODUCTION This paper outlines the development of a methodology, hereafter referred to as the Preliminary Zonal Safety Historically, system safety analysis was primarily based Analysis (PZSA).
    [Show full text]
  • Risk Assesment: Fault Tree Analysis
    RISK ASSESMENT: FAULT TREE ANALYSIS Afzal Ahmed+, Saghir Mehdi Rizvi*Zeshan Anwer Rana* Faheem Abbas* +COMSAT Institute of Information and Technology, Sahiwal, Pakistan *Navy Engineering College National University of Sciences and Technology, Islamabad drafzal@ciitsahiwal>edu.pk, 03452325972 ABSTRACT The failure of engineering equipment causes loss of capital as well as human loss, injuries, and stoppage of production line. The hazards can be classified as safe, minor, major, critical and catastrophic Risk analysis or hazard analysis pin points the potential failures of engineering systems and or components when being used.. Failure mode and effects analysis is used to identify hazard and to make system safer. A system is broken down up to level of components and using reliability data the safety or probability of failure of assemblies and the system can be calculated. The failure mode and effects analysis is used with fault tree analysis to point the areas of a complex system where failure mode effect analysis is required. Fault tree analysis (FTA) is a technique which pinpoints any failure or severe accidents. It tells how things fail rather than emphasize on the design performance. It is a logic diagram connecting inputs an outputs using Boolean algebra. This paper shows how FTA can be applied to car carburetor failure and car brake failure. Key words : Risk Management, Reliability, Fault tree, Failure mode INTRODUCTION The world is full risk. We are at risk of accident minor. A failure of an aircraft may cause death when crossing a road or driving. We are at risk to passengers, while a machine may cause living in an apartment not properly designed.
    [Show full text]
  • NASA Fault Tree Handbook with Aerospace Applications
    Fault Tree Handbook with Aerospace Applications Version 1.1 FFFaaauuulllttt TTTrrreeeeee HHHaaannndddbbbooooookkk wwwiiittthhh AAAeeerrrooossspppaaaccceee AAAppppppllliiicccaaatttiiiooonnnsss Prepared for NASA Office of Safety and Mission Assurance NASA Headquarters Washington, DC 20546 August, 2002 Fault Tree Handbook with Aerospace Applications Version 1.1 FFFaaauuulllttt TTTrrreeeeee HHHaaannndddbbbooooookkk wwwiiittthhh AAAeeerrrooossspppaaaccceee AAAppppppllliiicccaaatttiiiooonnnsss NASA Project Coordinators: Dr. Michael Stamatelatos, NASA Headquarters Office of Safety and Mission Assurance Mr. José Caraballo, NASA Langley Research Center Authors: NASA Dr. Michael Stamatelatos, NASA HQ, OSMA Lead Author: Dr. William Vesely, SAIC Contributing Authors (listed in alphabetic order): Dr. Joanne Dugan, University of Virginia Mr. Joseph Fragola, SAIC Mr. Joseph Minarick III, SAIC Mr. Jan Railsback, NASA JSC Fault Tree Handbook with Aerospace Applications Version 1.1 FFFaaauuulllttt TTTrrreeeeee HHHaaannndddbbbooooookkk wwwiiittthhh AAAeeerrrooossspppaaaccceee AAAppppppllliiicccaaatttiiiooonnnsss Acknowledgements The project coordinators and the authors express their gratitude to NASA Office of Safety and Mission Assurance (OSMA) management (Dr. Michael Greenfield, Deputy Associate Administrator and Dr. Peter Rutledge, Director of Enterprise Safety and Mission Assurance) and to Mr. Frederick Gregory, NASA Deputy Administrator, for their support and encouragement in developing this document. The authors also owe thanks to a number of reviewers
    [Show full text]
  • Hazard Analysis of Complex Spacecraft Using Systems- Theoretic Process Analysis *
    Hazard Analysis of Complex Spacecraft using Systems- Theoretic Process Analysis * Takuto Ishimatsu†, Nancy G. Leveson‡, John P. Thomas§, and Cody H. Fleming¶ Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 Masafumi Katahira#, Yuko Miyamoto**, and Ryo Ujiie†† Japan Aerospace Exploration Agency, Tsukuba, Ibaraki 305-8505, Japan Haruka Nakao‡‡ and Nobuyuki Hoshino§§ Japan Manned Space Systems Corporation, Tsuchiura, Ibaraki 300-0033, Japan Abstract A new hazard analysis technique, called System-Theoretic Process Analysis, is capable of identifying potential hazardous design flaws, including software and system design errors and unsafe interactions among multiple system components. Detailed procedures for performing the hazard analysis were developed and the feasibility and utility of using it on complex systems was demonstrated by applying it to the Japanese Aerospace Exploration Agency H-II Transfer Vehicle. In a comparison of the results of this new hazard analysis technique to those of the standard fault tree analysis used in the design and certification of the H-II Transfer Vehicle, System-Theoretic Hazard Analysis found all the hazardous scenarios identified in the fault tree analysis as well as additional causal factors that had not been) identified by fault tree analysis. I. Introduction Spacecraft losses are increasing stemming from subtle and complex interactions among system components. The loss of the Mars Polar Lander is an example [1]. The problems arise primarily because the growing use of software allows engineers to build systems with a level of complexity that precludes exhaustive testing and thus assurance of the removal of all design errors prior to operational use [2,3] Fault Tree Analysis (FTA) and Failure Modes and Effects Analysis (FMEA) were created long ago to analyze primarily electro-mechanical systems and identify potential losses due to component failure.
    [Show full text]
  • A Simulation Tool for Extended Dynamic Fault Trees
    DFTSim: A Simulation Tool for Extended Dynamic Fault Trees H. Boudali, A.P. Nijmeijer, M.I.A. Stoelinga University of Twente, CS Department, Enschede, NL. hboudali, andre, marielle @cs.utwente.nl { } Keywords: Dependability analysis, dynamic fault trees, simulation computation-time required to solve the DFT. tool, reliability benchmark. A simulation-based approach of standard DFTs has been sug- gested (but not implemented) in [11] as a possible solution tech- Abstract nique. In this paper, we propose DFTSim, a tool for simulating We present DFTSim, a simulation tool for dynamic fault trees (DFT). extended DFTs, where the input DFT file is compatible with the The simulation is carried out by directly sampling the failure distri- Galileo and the Coral textual DFT format. Such compatibility is butions attached to the leaves (called basic events) of the tree and indeed desired because it allows interoperability and integration propagating the failure times upwards in the tree. among these DFT tools. Sampling the distributions of the DFT leaves is however not ob- One of the major problems in DFT simulation-based approaches vious. To sample from the correct distributions, the analytical ex- is to sample from the correct distributions. In order to carry out such pression of the failure distributions of all basic events (BE) must be sampling the analytical expression of the failure distributions of all known. These are indeed known for non-spare BEs; but for spare basic events must be known. Such failure distributions are indeed BEs, they become conditional on the failure of other BEs. Hence, known for non-spare basic events; unfortunately, for spare basic the derivation of the analytical expression of the spares’ failure dis- events the failure distribution becomes conditional on the primary’s tributions and their sampling is not a trivial task.
    [Show full text]
  • An Overview of Fault Tree Analysis (FTA) Method for Reliability Analysis & Life Cycle Cost (LCC) Management
    IOSR Journal of Mechanical & Civil Engineering (IOSR-JMCE) ISSN: 2278-1684, PP: 14-18 www.iosrjournals.org An Overview of Fault Tree Analysis (FTA) Method for Reliability Analysis & Life Cycle Cost (LCC) Management Rajkumar B. Patil1, L. Y. Waghmode2, P. B. Chikali3, T. S. Mulla4. 1,3,4 ( Department of Mechanical Engineering ,Dr. J. J. Magdum College of Engineering, Jaysingpur, Shivaji University, Kolhapur, Maharashtra India). 2 ( Department of Mechanical Engineering, Annasaheb Dange College of Engineering and Technology, Ashta, Shivaji University, Kolhapur, Maharashtra(India). Abstract – Reliability analysis plays crucial role in the design process. In order to increase reliability of a system, analysis of failure data is essential. Fault Tree Analysis (FTA) is a method that directly focuses on the modes of failures. FTA is a graphical representation of the major faults or critical failures associated with a product and the causes for the faults and potential countermeasures. This paper presents the FTA of Lathe Machine. Qualitative and quantitative analysis helps to identify critical design parameters, maintenance suggestions. It also includes how reliability analysis fruitful for Life cycle cost management. Keywords – Fault Tree Analysis, FRACAS, Life Cycle Cost, MTBF, MTTF, Reliability Analysis. I.INTRODUCTION Reliability based design focuses on three terms as reliability, availability and maintainability. Reliability is defined to be the probability that the component or system will perform its intended functions for a specified period of time when used under stated operating conditions [1]. In simple words, reliability is nothing but the non-failure of the system over a given period of time. Reliability engineering is a sub-discipline within system engineering.
    [Show full text]
  • Booklet No. 15 Fault Tree Analysis
    Fault Tree Analysis Table of Contents Register of figures ................................................................................................................................... 3 1. Preface ............................................................................................................................................. 4 2. Introduction ..................................................................................................................................... 5 2.1. Objectives of the FTA .............................................................................................................. 5 2.2. History of the FTA .................................................................................................................... 5 2.3. Benefits and drawbacks of the FTA ......................................................................................... 5 2.3.1. Benefits of the method ................................................................................................... 5 2.3.2. Drawbacks of the method ............................................................................................... 6 2.4. FTA application areas .............................................................................................................. 6 3. Fundamentals of the FTA ................................................................................................................ 7 3.1. Roles .......................................................................................................................................
    [Show full text]
  • Probabilistic Safety Assessment for UAS Separation Assurance and Collision Avoidance Systems
    aerospace Article Probabilistic Safety Assessment for UAS Separation Assurance and Collision Avoidance Systems Asma Tabassum 1 , Roberto Sabatini 2,* and Alessandro Gardi 2 1 Department of Mechanical Engineering, University of North Dakota, Grand Forks, ND 58202, USA; [email protected] 2 School of Engineering, Aerospace Engineering and Aviation, RMIT University, Bundoora, VIC 3083, Australia; [email protected] * Correspondence: [email protected]; Tel.: +61-399-258-015 Received: 6 September 2018; Accepted: 17 January 2019; Published: 14 February 2019 Abstract: The airworthiness certification of aerospace cyber-physical systems traditionally relies on the probabilistic safety assessment as a standard engineering methodology to quantify the potential risks associated with faults in system components. This paper presents and discusses the probabilistic safety assessment of detect and avoid (DAA) systems relying on multiple cooperative and non-cooperative tracking technologies to identify the risk of collision of unmanned aircraft systems (UAS) with other flight vehicles. In particular, fault tree analysis (FTA) is utilized to measure the overall system unavailability for each basic component failure. Considering the inter-dependencies of navigation and surveillance systems, the common cause failure (CCF)-beta model is applied to calculate the system risk associated with common failures. Additionally, an importance analysis is conducted to quantify the safety measures and identify the most significant component
    [Show full text]
  • Model-Based Safety Analysis
    Model-Based Safety Analysis Anjali Joshi† Mats P.E. Heimdahl† Steven P. Miller‡ Mike W. Whalen‡ Department of Computer Science and Engineering† University of Minnesota 4-192 EE/SC Building 200 Union Street S.E. Minneapolis, Minnesota 55455 Advanced Technology Center‡ Rockwell Collins, Inc., 400 Collins Road NE, Cedar Rapids, IA 52498 USA Abstract System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.
    [Show full text]
  • Supporting the ARP4761 Safety Assessment Process with AADL
    Supporting the ARP4761 Safety Assessment Process with AADL Julien Delange and Peter Feiler Carnegie Melon Software Engineering Institute, 4500 5th Avenue, 15213 Pittsburgh, PA USA Abstract Cyber-physical systems, used in domains such as avionics or medical devices, perform critical functions where a fault might have catastrophic consequences (mission failure, severe injuries, etc.). Their development is guided by rigorous practice standards to avoid any error. However, as software importance continues to grow, integration and validation activities are becoming overwhelming. Late discovery of errors introduced in requirements and architecture design have resulted in costly rework, making up as much as 70% of the total software system cost. To overcome these issues, architecture-centric model-based approaches abstract system concerns into models that are analyzed to detect errors, issues or defects that are usually detected lately in the development process. This predictive analysis approach is automated by tools, avoiding any tedious manual efforts. In this paper, we present our model-based approach for capture and analyze system safety and reliability. We have added an error behavior annotation to SAE AADL, a standard for modeling embedded software system architectures. We also implemented analysis methods to automate safety analysis and production of safety assessment reports, as requested by safety recommended practices standards (such as ARP4761). Introduction Context Cyber-physical systems perform critical functions under constrained and potentially hostile circumstances. Because errors can have catastrophic consequences [12], they must be designed carefully and validated/certified according to a rigorous process to prove assurance of correct operation and increase confidence of system design. Verification criteria depend on applications criticality: the most demanding standards require validating and inspecting software code to prove evidence of behavior correctness.
    [Show full text]
  • Software Fault Tree Analysis for Safety Critical and Reliable Software
    PROTEUS JOURNAL ISSN/eISSN: 0889-6348 Software Fault Tree Analysis for Safety Critical and Reliable Software #1 Mr. S. P. Santhoshkumar, #2Mr. M. Praveen Kumar, #3Mr. T. Udhayakumar, #4Mr. S. Syed Shajahaan #1 Assistant Professor, Dept. of CSE, Rathinam Technical Campus, Coimbatore, Tamilnadu, India. #2,3,4 Assistant Professor, Dept. of IT, Rathinam Technical Campus, Coimbatore, Tamilnadu, India. Abstract —— U R Rao Satellite centre is the lead centre which will bring out failure modes at the early stage of the of ISRO, for building communication, remote sensing, development cycle like software requirement specification or navigation, and inter planetary missions. Software plays software design specification. This stage is more important a major role in satellite functionalities. The complexity of as it will not allow the faults to propagate to next phase in the software is increasing from spacecraft to spacecraft. the SDLC which is expensive and time consuming. Hence Requirements has to be classified into safety critical and SFTA helps in achieving better fault tolerant systems. Soft non-safety critical. The critical software has to be emergency check and voltage control logics are used for analysed in a different way. To achieve high reliability shedding path of Thresholds. Load Shedding check is done software safety standards and guidelines has to be on the basis of comparison of battery voltage with thresholds followed strictly. The quality and reliability of the A, B, C, D, E and F. SFTA is applied to all the thresholds. software can be achieved by applying technique like For every comparison there are possible outcomes and based PHA, SFTA, SFMEA.
    [Show full text]
  • Guide to Reusable Launch and Reentry Vehicle Reliability Analysis
    Guide to Reusable Launch and Reentry Vehicle Reliability Analysis Federal Aviation Administration Associate Administrator for Commercial Space Transportation 800 Independence Avenue, Room 331 Washington, DC 20591 Version 1.0 April 2005 Guide to Reusable Launch and Reentry Vehicle Reliability Analysis Version 1.0 April 2005 Federal Aviation Administration Associate Administrator for Commercial Space Transportation 800 Independence Avenue, Room 331 Washington, DC 20591 NOTICE Use of trade names or names of manufacturers in this document does not constitute an official endorsement of such products or manufacturers, either expressed or implied, by the Federal Aviation Administration. TABLE OF CONTENTS 1.0 INTRODUCTION......................................................................................................... 1 1.1 Purpose.................................................................................................................. 1 1.2 Scope ..................................................................................................................... 1 1.3 Authority ............................................................................................................... 2 2.0 DEFINITIONS AND ACRONYMS............................................................................. 2 2.1 Definitions............................................................................................................. 2 2.2 Acronyms .............................................................................................................
    [Show full text]