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Reliability Assessment of Safety-Critical Network Communication in a Digitalized Nuclear Power Plant

In analog instrumentation and control (I and C) systems for nuclear power plants (NPPs), most connections are comprised of hardwired point-to-point types. Since they are based on analog technologies, they are fragile to noise and require analog-to-digital conversion time. Therefore, many NPPs have adopted communication network for the exchange of safety-critical data between programmable logic controllers (PLCs) in digital I and C systems to effectively accommodate a huge number of field controllers. However, the primary issue of digital network communication in a safety-critical system involves potential hazards, such as partial or total loss of communication between PLCs, which may result in a failure of safety critical signal generation when it is needed. Therefore, the probability that a safety-critical system in digitalized NPP becomes unsafe due to a network failure must be evaluated to quantify the risk of digital I and C system. In Korea, the Engineered Safety Feature-Component Control System (ESF-CCS) was developed as one of the digital safety-critical system in Advanced Power Reactor- 1400 (APR-1400). The function of a digital engineered safety feature (ESF) actuation system and field actuator controllers of conventional NPPs are performed by the ESF-CCS. In this system, safety-critical network, High Reliable- Safety Data Network (HR-SDN), was employed for the safety-critical data transmission from group controllers (GCs) to loop controllers (LCs). In this study, a framework for assessing the reliability of a HR-SDN network communication between GCs and LCs in the ESF-CCS in addition to a fault-tree model for ESF components considering network failure between GCs and LCs were developed to assess the plant risk effect of a newly developed digitalized ESF-CCS. Based on the case studies and cut set analysis, the risk effect of network failure on plant risk and the important risk contributors of network failure were quantitatively addressed. A framework for identifying the potential hazardous states of network communication in the ESFCCS was proposed. In addition, a fault-tree model for network communication failure was developed to estimate the risk effects of network failure between the GCs and LCs on ESF-CCS signal failure. The developed fault-tree model was then applied to several case studies. The fault-tree model of ESF-CCS signal failure for ESF components required for various mitigation actions regarding NPP DBAs was designed by considering the identified hazardous states of network failure that would result in a failure to provide input signals to the corresponding LC. As a sensitivity study, three case studies were performed based on the periodic test methods for hardware components in HR-SDN module and their test intervals in this study. The quantitative results for three case studies demonstrated that the probability of overall network communication failure, which was calculated as the sum of the failure probability associated with each failure cause, contributed up to 1.58% on the Small-LOCA CD frequency. The results also revealed the important basic events related to network failure in the case studies which included CCF of hardware and software in HR-SDN module. This study is expected to provide insight into the development of the fault-tree model for the network failure in digital I and C system and into the quantification of the risk effect of network failure for safety-critical data transmission in NPPs. As a further study, the risk effects of network failure in the ESF-CCS on the plant risk can be estimated in a more detailed manner by analyzing the failure modes and causes in a sub-component level and the fault detection coverage of the fault tolerance techniques for network failure implemented in ESF-CCS after the detailed configuration of ESF-CCS is decided. In terms of the failure of manual ESF actuation, the relationship among the human action failures must be investigated to consider multiple human error condition since ESF-CCS provides multiple manual actuation to assure the diversity of the system. Since the conventional HEP method cannot accommodate the multiple conditions in a fault tree, condition-based human reliability assessment (CBHRA) method or the dynamic human reliability modeling approach can be applied to include a complex relationship among the automated safety signal generation and the human operator's manual actuation, avoiding the optimistic estimation of HEP of the human action failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Conversion of Questionnaire Data

During the survey, respondents are asked to provide qualitative answers (well, adequate, needs improvement) on how well material control and accountability (MC&A) functions are being performed. These responses can be used to develop failure probabilities for basic events performed during routine operation of the MC&A systems. The failure frequencies for individual events may be used to estimate total system effectiveness using a fault tree in a probabilistic risk analysis (PRA). Numeric risk values are required for the PRA fault tree calculations that are performed to evaluate system effectiveness. So, the performance ratings in the questionnaire must be converted to relative risk values for all of the basic MC&A tasks performed in the facility. If a specific material protection, control, and accountability (MPC&A) task is being performed at the 'perfect' level, the task is considered to have a near zero risk of failure. If the task is performed at a less than perfect level, the deficiency in performance represents some risk of failure for the event. As the degree of deficiency in performance increases, the risk of failure increases. If a task that should be performed is not being performed, that task is in a state of failure. The failure probabilities of all basic events contribute to the total system risk. Conversion of questionnaire MPC&A system performance data to numeric values is a separate function from the process of completing the questionnaire. When specific questions in the questionnaire are answered, the focus is on correctly assessing and reporting, in an adjectival manner, the actual performance of the related MC&A function. Prior to conversion, consideration should not be given to the numeric value that will be assigned during the conversion process. In the conversion process, adjectival responses to questions on system performance are quantified based on a log normal scale typically used in human error analysis (see A.D. Swain and H.E. Guttmann, 'Handbook of Human Reliability Analysis with Emphasis on Nuclear Power Plant Applications,' NUREG/CR-1278). This conversion produces the basic event risk of failure values required for the fault tree calculations. The fault tree is a deductive logic structure that corresponds to the operational nuclear MC&A system at a nuclear facility. The conventional Delphi process is a time-honored approach commonly used in the risk assessment field to extract numerical values for the failure rates of actions or activities when statistically significant data is absent.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Linking classical PRA models to a dynamic PRA

Here, this paper presents a series of methods designed to incorporate classical Probabilistic Risk Assessment (PRA) models such as Event Trees (ETs) and Fault Trees (FTs) into dynamic PRA. In contrast to classical PRA, dynamic PRA couples stochastic methods with system simulators to determine the risks associated with complex systems such as nuclear power plants. Compared with classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the progression of the accident. As part of a dynamic PRA analysis, it is not uncommon that parts of the system to be analyzed might not require a computationally expensive simulation model. These parts could be in fact modeled by employing classical PRA models (e.g., a FT). Here, we present a set of methods and tools that can be used to link the most common classical PRA models (ETs, FTs, reliability block diagrams and Markov models) to simulation codes such as RELAP5-3D: creating a “hybrid PRA.” In order to show the potential of such an hybrid PRA we employ this method to verify ET modeling assumptions (e.g., success criteria) using a large break loss of coolant accident initiating event as a test case. In this respect, we link a set of FTs from the original PRA to the RELAP5-3D code and perform a hybrid PRA. The FTs are employed to model the control logic of several safety systems and to propagate component failures throughout the system. Provided the generated dynamic PRA data, we show how conservative assumptions in the original PRA can be identified and how such original PRA can be modified by updating success criteria captured by the set of RELAP5-3D simulation runs.

97 - MATHEMATICS AND COMPUTING↗

Comparative analysis of techniques for evaluating the effectiveness of aircraft computing systems

Performability analysis is a technique developed for evaluating the effectiveness of fault-tolerant computing systems in multiphase missions. Performability was evaluated for its accuracy, practical usefulness, and relative cost. The evaluation was performed by applying performability and the fault tree method to a set of sample problems ranging from simple to moderately complex. The problems involved as many as five outcomes, two to five mission phases, permanent faults, and some functional dependencies. Transient faults and software errors were not considered. A different analyst was responsible for each technique. Significantly more time and effort were required to learn performability analysis than the fault tree method. Performability is inherently as accurate as fault tree analysis. For the sample problems, fault trees were more practical and less time consuming to apply, while performability required less ingenuity and was more checkable. Performability offers some advantages for evaluating very complex problems.

Hitt, E. F.↗

Dynamic PRA Methods to Evaluate the Impact on Accident Progression of Accident Tolerant Fuels

Accident tolerant fuels (ATFs) are new nuclear fuels developed in response to the accident at the Fukushima power station in March 2011. The goal of ATFs is to withstand accident scenarios through better performance compared to currently employed fuels (e.g., small-scale hydrogen generation). This paper targets a method for evaluating and comparing ATF performance from a probabilistic risk assessment (PRA) perspective by employing a newly developed combination of event trees and dynamic PRA methods. Compared to classical PRA methods based on event trees and fault trees, dynamic PRA can evaluate with higher resolution the safety impacts of physics dynamics and the timing/sequencing of events on the accident progression without the need to introduce overly conservative modeling assumptions and success criteria. In this paper, we analyze the impact on the accident progression of three different cladding configurations for two initiating events [a large break loss-of-coolant accident (LB-LOCA) and a station blackout (SBO)] by employing dynamic PRA methods. The goal is to compare the safety performance of ATFs (FeCrAl and Cr-coated cladding) and the currently employed Zr-based clad fuel. We employ two different strategies. The first focuses on the identification of success criteria discrepancies between the accident sequences generated by the classical PRA model and the set of simulation runs generated by dynamic PRA using ATF. The second one, on the other hand, directly uses dynamic PRA to evaluate the impact of timing of events (e.g., recovery actions) on accident progression. In conclusion, by applying these methods to the LB-LOCA and SBO initiating events, we show how dynamic PRA methods can provide analysts with detailed and quantitative information on the safety impact of ATFs.

97 - MATHEMATICS AND COMPUTING↗

Constellation Probabilistic Risk Assessment (PRA): Design Consideration for the Crew Exploration Vehicle

Managed by NASA's Office of Safety and Mission Assurance, a pilot probabilistic risk analysis (PRA) of the NASA Crew Exploration Vehicle (CEV) was performed in early 2006. The PRA methods used follow the general guidance provided in the NASA PRA Procedures Guide for NASA Managers and Practitioners'. Phased-mission based event trees and fault trees are used to model a lunar sortie mission of the CEV - involving the following phases: launch of a cargo vessel and a crew vessel; rendezvous of these two vessels in low Earth orbit; transit to th$: moon; lunar surface activities; ascension &om the lunar surface; and return to Earth. The analysis is based upon assumptions, preliminary system diagrams, and failure data that may involve large uncertainties or may lack formal validation. Furthermore, some of the data used were based upon expert judgment or extrapolated from similar components~systemsT. his paper includes a discussion of the system-level models and provides an overview of the analysis results used to identify insights into CEV risk drivers, and trade and sensitivity studies. Lastly, the PRA model was used to determine changes in risk as the system configurations or key parameters are modified.

Prassinos, Peter G.↗

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.

Guarro, Sergio B.↗

Modeling In-Space Aborts for NASA Human Exploration Missions

NASA is developing new capabilities to send humans beyond low Earth orbit (LEO) for the first time in several decades with the new Multi-purpose Crew Vehicle (MPCV) Orion spacecraft and Space Launch System (SLS) launch vehicle. As part of these capabilities, NASA is developing means to terminate missions prior to reaching mission destinations in order to save the crew in the event of critical life-threatening failures. This abort capability exists for both ascent and in-space operations. While the risk associated with ascent aborts has been modeled in detail, less has been done in the area of in-space aborts (e.g. Apollo 13). Recent efforts have started to better assess the risk associated with in-space aborts. This paper will describe these efforts. The in-space abort model described in this paper is part of a larger Cross-Program PRA (XPRA) model of exploration missions planned in the next few years to the vicinity of the Moon. The model consists of linked event trees and fault trees and associated rules built using the Systems Analysis Program for Hands-On Integrated Reliability Evaluations (SAPHIRE) tool. This model structure is being built with flexibility in mind in order to perform risk trades and further expansion of the model.

Bigler, Mark A.↗

DYNAMIC PRA OF A MULTI-UNIT PLANT

Dynamic Probabilistic Risk Analysis (PRA) methods couple stochastic methods (e.g., RAVEN, ADAPT, ADS, MCDET) with safety analysis codes (RELAP5-3D, MELCOR, MAAP) to determine risk associated to complex systems such as nuclear plants. Compared to classical PRA methods, which are based on static logic structures (e.g., Event-Trees, Fault-Trees), they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. Recently, special attention has been given to nuclear plants which consist of multiple units and, in particular, on the safety impact of system dependencies, shared systems and common resources on core damage frequencies. In the literature, while classical PRA methods have been employed to model multi-unit plants, Dynamic PRA methods have never been applied to analyze a full multi-unit model. This paper presents a PRA analysis of a multi-unit plant using Dynamic PRA methods. We employ RAVEN as stochastic method coupled with RELAP5-3D. The plant under consideration consists of the three units and their associated spent fuel pools (SFPs). The studied initiating event is a seismic induced station blackout event. We will describe in detail how the multi-unit plant has been constructed and, in particular, how unit dependencies and shared resources are modeled.

97 MATHEMATICS AND COMPUTING↗

Use of simplified PSA studies in support of the ASTRID design process

In the framework of the French Act of 28 June 2006 about nuclear materials and waste management, a GEN IV and actinides incineration demonstration prototype is to be commissioned in the 2020 decade. In this objective a prototype called ASTRID (Advanced Sodium Technological Reactor for Industrial Demonstration) is proposed to demonstrate the progress made in SFR technology at an industrial scale by qualifying innovative options, some of which still remain open in the areas requiring improvements, especially safety and operability. More specifically, we aim for a level of safety that is at least equivalent to that of the EPR (third generation), with improvements made in SFR-specific fields. The integration of safety issues in the early phase of the design of ASTRID is necessarily expected. For this purpose, CEA and its partners AREVA and EDF have planned to perform a level-1 PSA to support and orientate the preliminary design of ASTRID reactor. This paper presents the PSA approach and current studies for the assessment of safety systems and the future work to be done for the 2012-2014 period. The preliminary preparation of PSA studies is presented: objectives and scope of the early design phase PSA, definition of core damage states, selection and grouping of initiating events, assessment of safety functions and related systems. Work under progress is also presented: modelling of event trees, construction of fault trees of safety systems, transient calculations of accident sequences with the CATHARE2 code and reliability data assessment. Main objectives of a level-1 PSA performed at conceptual design stage are an early assessment of the safety architecture of the reactor and findings about the most effective areas for improvement, but also the identification of dominant accident sequences and comparison with alternative designs. After the elaboration of a simplified level-1 PSA model for nominal state and main internal initiators, various design alternatives will be evaluated from the viewpoint of PSA in order to support the design choices of the ASTRID reactor. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA

In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA

In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Columbia Accident Investigation Board Report. Volume Two

Volume II of the Report contains appendices that were cited in Volume I. The Columbia Accident Investigation Board produced many of these appendices as working papers during the investigation into the February 1, 2003 destruction of the Space Shuttle Columbia. Other appendices were produced by other organizations (mainly NASA) in support of the Board investigation. In the case of documents that have been published by others, they are included here in the interest of establishing a complete record, but often at less than full page size. Contents include: CAIB Technical Documents Cited in the Report: Reader's Guide to Volume II; Appendix D. a Supplement to the Report; Appendix D.b Corrections to Volume I of the Report; Appendix D.1 STS-107 Training Investigation; Appendix D.2 Payload Operations Checklist 3; Appendix D.3 Fault Tree Closure Summary; Appendix D.4 Fault Tree Elements - Not Closed; Appendix D.5 Space Weather Conditions; Appendix D.6 Payload and Payload Integration; Appendix D.7 Working Scenario; Appendix D.8 Debris Transport Analysis; Appendix D.9 Data Review and Timeline Reconstruction Report; Appendix D.10 Debris Recovery; Appendix D.11 STS-107 Columbia Reconstruction Report; Appendix D.12 Impact Modeling; Appendix D.13 STS-107 In-Flight Options Assessment; Appendix D.14 Orbiter Major Modification (OMM) Review; Appendix D.15 Maintenance, Material, and Management Inputs; Appendix D.16 Public Safety Analysis; Appendix D.17 MER Manager's Tiger Team Checklist; Appendix D.18 Past Reports Review; Appendix D.19 Qualification and Interpretation of Sensor Data from STS-107; Appendix D.20 Bolt Catcher Debris Analysis.

CAIB (COLUMBIA ACCIDENT INVESTIGATION BOARD)↗

A systematic risk management approach employed on the CloudSat project

The CloudSat Project has developed a simplified approach for fault tree analysis and probabilistic risk assessment. A system-level fault tree has been constructed to identify credible fault scenarios and failure modes leading up to a potential failure to meet the nominal mission success criteria.

risk management fault tree analysis probabilistic ↗

A graphical language for reliability model generation

A graphical interface capability of the hybrid automated reliability predictor (HARP) is described. The graphics-oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault tree gates, including sequence dependency gates, or by a Markov chain. With this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the Graphical Kernel System (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing.

Howell, Sandra V.↗

Graphical workstation capability for reliability modeling

In addition to computational capabilities, software tools for estimating the reliability of fault-tolerant digital computer systems must also provide a means of interfacing with the user. Described here is the new graphical interface capability of the hybrid automated reliability predictor (HARP), a software package that implements advanced reliability modeling techniques. The graphics oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault-tree gates, including sequence-dependency gates, or by a Markov chain. By using this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain, which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the graphical kernal system (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing stages.

Bavuso, Salvatore J.↗

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗

TU-AB-BRD-00: Task Group 100

Current quality assurance and quality management guidelines provided by various professional organizations are prescriptive in nature, focusing principally on performance characteristics of planning and delivery devices. However, published analyses of events in radiation therapy show that most events are often caused by flaws in clinical processes rather than by device failures. This suggests the need for the development of a quality management program that is based on integrated approaches to process and equipment quality assurance. Industrial engineers have developed various risk assessment tools that are used to identify and eliminate potential failures from a system or a process before a failure impacts a customer. These tools include, but are not limited to, process mapping, failure modes and effects analysis, fault tree analysis. Task Group 100 of the American Association of Physicists in Medicine has developed these tools and used them to formulate an example risk-based quality management program for intensity-modulated radiotherapy. This is a prospective risk assessment approach that analyzes potential error pathways inherent in a clinical process and then ranks them according to relative risk, typically before implementation, followed by the design of a new process or modification of the existing process. Appropriate controls are then put in place to ensure that failures are less likely to occur and, if they do, they will more likely be detected before they propagate through the process, compromising treatment outcome and causing harm to the patient. Such a prospective approach forms the basis of the work of Task Group 100 that has recently been approved by the AAPM. This session will be devoted to a discussion of these tools and practical examples of how these tools can be used in a given radiotherapy clinic to develop a risk based quality management program. Learning Objectives: Learn how to design a process map for a radiotherapy process Learn how to perform failure modes and effects analysis analysis for a given process Learn what fault trees are all about Learn how to design a quality management program based upon the information obtained from process mapping, failure modes and effects analysis and fault tree analysis. Dunscombe: Director, TreatSafely, LLC and Center for the Assessment of Radiological Sciences; Consultant to IAEA and Varian Thomadsen: President, Center for the Assessment of Radiological Sciences Palta: Vice President of the Center for the Assessment of Radiological Sciences.

60 APPLIED LIFE SCIENCES↗