Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “root cause analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

MO-F-16A-04: Case Study: Estimation of Peak Skin Dose Following a Physician Reported “High Dose” Case and Sentinel Event Considerations

Purpose: This work offers as a teaching example a reported high dose fluoroscopy case and the workflow the institution followed to self-report a radiation overdose sentinel event to the Joint Commission. Methods: Following the completion of a clinical case in a hybrid OR room with a reported air kerma of >18 Gy at the Interventional Reference Point (IRP) the physicians involved in the case referred study to the institution's Radiation Safety Committee (RSC) for review. The RSC assigned a Diagnostic Medical Physicist (DMP) to estimate the patient's Peak Skin Dose (PSD) and analyze the case. Following the DMP's analysis and estimate of a PSD of >15 Gy the institution's adverse event committee was convened to discuss the case and to self-report the case as a radiation overdose sentinel event to the Joint Commission. The committee assigned a subgroup to perform the root cause analysis and develop institutional responses to the event. Results: The self-reporting of the sentinel event and the associated root cause analysis resulted in several institutional action items that are designed to improve process and safety. A formal reporting and analysis mechanism was adopted to review fluoroscopy cases with air kerma greater than 6 Gy at the IRP. An improved and formalized radiation safety training program for physicians using fluoroscopy equipment was implemented. Additionally efforts already under way to monitor radiation exposure in the Radiology department were expanded to include all fluoroscopy equipment capable of automated dose reporting. Conclusion: The adverse event review process and the root cause analysis following the self-reporting of the sentinel event resulted in policies and procedures that are expected to improve the quality and safe usage of fluoroscopy throughout the institution.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2006

A Perspective on DSN System Performance Analysis

This paper discusses the performance analysis effort being carried out in the NASA Deep Space Network. The activity involves root cause analysis of failures and assessment of key performance metrics. The root cause analysis helps pinpoint the true cause of observed problems so that proper correction can be effected. The assessment currently focuses on three aspects: (1) data delivery metrics such as Quantity, Quality, Continuity, and Latency; (2) link-performance metrics such as antenna pointing, system noise temperature, Doppler noise, frequency and time synchronization, wide-area-network loading, link-configuration setup time; and (3) reliability, maintainability, availability metrics. The analysis establishes whether the current system is meeting its specifications and if so, how much margin is available. The findings help identify the weak points in the system and direct attention of programmatic investment for performance improvement.

Deep Space Network (DSN)↗
NASA NTRS2018

Printed Circuit Board Inspection and Quality Control - PCB Failure Causes and Cures

This two day workshop will discuss a range of topics, including root cause analysis, physics-of-failure principles and failure mechanisms in printed circuit boards. Printed circuit boards (PCBs) are the baseline for electronics manufacturing upon which electronic components are mounted and formed into electronic systems. PCBs are used in a variety of electronic circuits from simple one-transistor amplifiers to large super computers. A PCB serves three main functions: 1) it provides the necessary mechanical support for the components in the circuit 2) it provides the necessary electrical interconnections, and 3) it bears some form of legend which identifies the components it carries. The failure modes on the PCBs can be categorized in a hierarchical structure, in which the mechanisms and causes are site or location dependant. Specimen preparation techniques, non-destructive and destructive analysis, and materials characterization will also be discussed. The first day of the workshop will present methodologies for identifying potential failure mechanisms in electronics based on the failure history and, systematic approaches to root cause analysis. The second day will cover failure analysis techniques geared towards various failure mechanisms, along with numerous component and PCB assembly failure analysis case studies that illustrate the techniques and analysis. Failure analysis case studies will be used to illustrate the techniques and analysis principles to arrive at the root cause(s) of field failures on printed circuit boards, active components, and assemblies.

Printed circuit boards↗
NASA NTRS2006

Quality Interaction Between Mission Assurance and Project Team Members

Mission Assurance independent assessments started during the development cycle and continued through post launch operations. In operations, Health and Safety of the Observatory is of utmost importance. Therefore, Mission Assurance must ensure requirements compliance and focus on process improvements required across the operational systems including new/modified products, tools, and procedures. The deployment of the interactive model involves three objectives: Team member Interaction, Good Root Cause Analysis Practices, and Risk Assessment to avoid reoccurrences. In applying this model, we use a metric based measurement process and was found to have the most significant effect, which points to the importance of focuses on a combination of root cause analysis and risk approaches allowing the engineers the ability to prioritize and quantify their corrective actions based on a well-defined set of root cause definitions (i.e. closure criteria for problem reports), success criteria and risk rating definitions.

quality↗
DOE OSTI2015

Monitoring Extreme-scale Lustre Toolkit

We discuss the design and ongoing development of the Monitoring Extreme-scale Lustre Toolkit (MELT), a unified Lustre performance monitoring and analysis infrastructure that provides continuous, low-overhead summary information on the health and performance of Lustre, as well as on-demand, in-depth problem diagnosis and root-cause analysis. The MELT infrastructure leverages a distributed overlay network to enable monitoring of center-wide Lustre filesystems where clients are located across many network domains. We preview interactive command-line utilities that help administrators and users to observe Lustre performance at various levels of resolution, from individual servers or clients to whole filesystems, including job-level reporting. Finally, we discuss our future plans for automating the root-cause analysis of common Lustre performance problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Validation Progress and Plans for ENDF/B-VIII.1β1 at ORNL [Slides]

This presentation opens with a ORNL definition of ENDF/B-VIII.1β1. Following with keff results for CE calculations with VALID. Additionally provided are Preliminary Root Cause Analysis (RCA) results. This presentation then concludes with future plans for additional validation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

TH-B-BRC-00: How to Identify and Resolve Potential Clinical Errors Before They Impact Patients Treatment: Lessons Learned

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-B-BRC-01: How to Identify and Resolve Potential Clinical Errors

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-B-BRC-02: Troubleshooting Issues with Linear Accelerator

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-B-BRC-03: Measurement and Calibration Discrepancy: Advanced Warning Guidance

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2008

Integrated System Health Management (ISHM) for Test Stand and J-2X Engine: Core Implementation

ISHM capability enables a system to detect anomalies, determine causes and effects, predict future anomalies, and provides an integrated awareness of the health of the system to users (operators, customers, management, etc.). NASA Stennis Space Center, NASA Ames Research Center, and Pratt & Whitney Rocketdyne have implemented a core ISHM capability that encompasses the A1 Test Stand and the J-2X Engine. The implementation incorporates all aspects of ISHM; from anomaly detection (e.g. leaks) to root-cause-analysis based on failure mode and effects analysis (FMEA), to a user interface for an integrated visualization of the health of the system (Test Stand and Engine). The implementation provides a low functional capability level (FCL) in that it is populated with few algorithms and approaches for anomaly detection, and root-cause trees from a limited FMEA effort. However, it is a demonstration of a credible ISHM capability, and it is inherently designed for continuous and systematic augmentation of the capability. The ISHM capability is grounded on an integrating software environment used to create an ISHM model of the system. The ISHM model follows an object-oriented approach: includes all elements of the system (from schematics) and provides for compartmentalized storage of information associated with each element. For instance, a sensor object contains a transducer electronic data sheet (TEDS) with information that might be used by algorithms and approaches for anomaly detection, diagnostics, etc. Similarly, a component, such as a tank, contains a Component Electronic Data Sheet (CEDS). Each element also includes a Health Electronic Data Sheet (HEDS) that contains health-related information such as anomalies and health state. Some practical aspects of the implementation include: (1) near real-time data flow from the test stand data acquisition system through the ISHM model, for near real-time detection of anomalies and diagnostics, (2) insertion of the J-2X predictive model providing predicted sensor values for comparison with measured values and use in anomaly detection and diagnostics, and (3) insertion of third-party anomaly detection algorithms into the integrated ISHM model.

Figueroa, Jorge F.↗
NASA NTRSDate not supplied

Structural Dynamics Observations in Space Launch System Green Run Hot Fire Testing

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. The Green Run Hot Fire (GRHF) of the SLS Core Stage provided a flight-like ground test environment for verification of integrated vehicle TVC performance. A TVC model coupled to a vehicle structural dynamic model has been developed previously and incrementally validated in subsystem tests and simulations. Still, some aspects of TVC performance in GRHF were not anticipated. The ensuing investigation demonstrated the need for well-instrumented test environments, various levels of modeling fidelity, test-representative structural models, and caution in reuse of legacy components. This paper is the sixth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. It introduces the salient structural dynamic phenomena uncovered in ambient and hot fire testing. During the Green Run test campaign, a comparison of ambient and hot fire step responses showed a significant change in apparent damping due to the presence of friction, challenging long standing assumptions that friction could be neglected. Additionally, the characteristic response of the engine and thrust structure during GRHF proved to be more complex than anticipated, as evidenced by the available actuator, thrust structure, and engine measurements. While the string-potentiometer based test instrumentation was intended to allow for reconstruction of the engine angles along the two control axes, the geometric placement, location uncertainty, and responses in overlapping frequency spectra revealed additional phenomena requiring further analysis and post-processing. The observations from both modal and frequency response testing during the Green Run ambient and hot fire configurations led to Engine and Core Stage FEM (finite element model) updates. When evidence of unexpected engine motion was found in engine section accelerometer data, the authors pursued additional structural analysis leading to FEM updates associated with the TVC gimbal and thrust structure. Through collaboration between structures, TVC, and flight control disciplines, the test-informed models and root-cause analysis led to confident flight rationale for the first flight of the SLS launch vehicle.

Richard K. Moore↗
NASA NTRSDate not supplied

Structural Dynamics Observations in Space Launch System Green Run Hot Fire Testing

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. The Green Run Hot Fire (GRHF) of the SLS Core Stage provided a flight-like ground test environment for verification of integrated vehicle TVC performance. A TVC model coupled to a vehicle structural dynamic model has been developed previously and incrementally validated in subsystem tests and simulations. Still, some aspects of TVC performance in GRHF were not anticipated. The ensuing investigation demonstrated the need for well-instrumented test environments, various levels of modeling fidelity, test-representative structural models, and caution in reuse of legacy components. This paper is the sixth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. It introduces the salient structural dynamic phenomena uncovered in ambient and hot fire testing. During the Green Run test campaign, a comparison of ambient and hot fire step responses showed a significant change in apparent damping due to the presence of friction, challenging long standing assumptions that friction could be neglected. Additionally, the characteristic response of the engine and thrust structure during GRHF proved to be more complex than anticipated, as evidenced by the available actuator, thrust structure, and engine measurements. While the string-potentiometer based test instrumentation was intended to allow for reconstruction of the engine angles along the two control axes, the geometric placement, location uncertainty, and responses in overlapping frequency spectra revealed additional phenomena requiring further analysis and post-processing. The observations from both modal and frequency response testing during the Green Run ambient and hot fire configurations led to Engine and Core Stage FEM (finite element model) updates. When evidence of unexpected engine motion was found in engine section accelerometer data, the authors pursued additional structural analysis leading to FEM updates associated with the TVC gimbal and thrust structure. Through collaboration between structures, TVC, and flight control disciplines, the test-informed models and root-cause analysis led to confident flight rationale for the first flight of the SLS launch vehicle.

Richard Moore↗
DOE OSTI2019

System Deterioration Detection and Root Cause Learning on Time Series Graphs

System deterioration detection and root cause analysis is crucial for today's industrial society. However, the design and operation of mechanic system is getting more and more complex, which makes it hard at identifying deterioration with noisy data. Our research focus on solving such problem on time-evolving sensor graphs in a streaming setting. Given a sequence of graphs, the ability to identify 1) any gradual and stable structured change and 2) the root cause components is of importance for early warning and system diagnosis. Existing methods either raise too many false alerts on instant changes or are too sensitive to noise. To address these problems, we propose Robust Failure Detection and Diagnosis (RoFaD). RoFaD can capture failure propagation given a time series of graph. By optimizing a matrix based Taylor expansion, RoFaD can identify system deterioration in the presence of noise and immediate changes, and diagnose the root cause components. Experiments on both synthetic and real world datasets demonstrate that RoFaD is more effective than the popular baselines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Limited Characterization of Wind Turbine Adhesives [EPIKOTE Resin MGS BPR 135G3/EPIKURE Curing Agent MGS RIMH 134 (H134i) and MGS BP20/EPIKURE Curing Agent MGS BPH 20 (rework adhesive)] and Root Insert Exterior Surface.

The National Rotor Testbed (NRT) is a wind turbine blade research program in the Sandia National Laboratories (SNL) Wind Department that has developed a new blade design. Each blade includes bonded-in, threaded metal root inserts that enable the blades to be bolted onto the wind turbine hub. Prior to installing the flight blades on the turbine, root insert strength verification tests exhibited a subset of failures below the design load on one (NRT-02) of four blades. As part of a root cause analysis for the failures, this work analyzes "scraps" of the epoxy adhesive used to bond the metal inserts into the blade and uses surface topography and x-ray fluorescence (XRF) measurements to characterize the exterior surface of the root insert. Samples were taken from inserts that exhibited both high and low loads at failure, as well as some "control inserts" to monitor the state of the surface throughout the manufacturing process. Differences in the calorimetric response of the adhesive from the separate root inserts are apparent but none of them appear to relate to the pull load required to dislodge the inserts. Two takeaways of note include: In the way that the adhesive is processed, it does not reach full cure; and, Something occurred to sample#10 such that the fully-cured adhesive has a significantly lower T g .

17 WIND ENERGY↗
DOE OSTI2019

Failure Analysis on Multivariate Time-series Data given Uncertain Labels

Machine failure analysis and detection is critical to today’s industrial society. Given a number of failure events on multivariate temporal data, the ability to identify 1) the discriminative patterns prior to the events and 2) the most relevant features to the failure has practical use for early warning and root cause analysis. However, since these patterns are not necessarily adjacent to the onset of failure in time, faulty labels are often with uncertainty, which makes traditional supervised detection methods inapplicable. To address the label uncertainty and learn the complicated correlation in multivariate time series, we design Failure Analysis on Multivariate Time-series Data (MAMT) that jointly selects the most failure-relevant features and time-instances by a novel dynamic and directional label diffusion process. Extensive experiments demonstrate that MAMT is more effective while more efficient than popular baselines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

TU-C-BRE-01: KEYNOTE PRESENTATION - Emerging Frontiers in IMRT QA

As IMRT treatment processes advance and mature, so must the quality assurance processes being used to validate their delivery. In some respects, treatment delivery advancements (e.g. VMAT) have out-paced QA advancements. The purpose of this session is to describe new processes that are being implemented to bring IMRT QA up-to-date with the treatment delivery advances. It would explore emerging IMRT QA paradigms, including requirements-based IMRT QA which necessitates definition of delivery errors (e.g. patient dose error, leaf positioning error) and development of processes to ensure reliable error detection. Engineeringbased QA approaches, including use of IMRT treatment delivery process trees, fault tree analysis and failure modes effects analysis would be described. Approaches to detect errors such as (1) during treatment delivery validation using exit fluence detectors (e.g. EPIDs); (2) analysis of treatment delivery via use of machine parameter log files; (3) dose recalculation using (3a) treatment planning system; (3b) record-and-verify; or (3c) entrance and exit fluence measurement parameters would be explained. The relative advantages and disadvantages of each method would be discussed. Schemes for error classification and root cause analysis would be described – steps which are essential for future error prevention. For each QA method, testing procedures and results would be presented indicating the types of errors that can be detected, those that cannot be detected, and the reliability of the error detection method (for example determined via ROC analysis). For speakers, we are seeking to engage non-commercially biased experts. Those listed below are a sub-sample of possible qualified individuals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Fault localization in a microfabricated surface ion trap using diamond nitrogen-vacancy center magnetometry

Here, as quantum computing hardware becomes more complex with ongoing design innovations and growing capabilities, the quantum computing community needs increasingly powerful techniques for fabrication failure root-cause analysis. This is especially true for trapped-ion quantum computing. As trapped-ion quantum computing aims to scale to thousands of ions, the electrode numbers are growing to several hundred, with likely integrated photonic components also adding to the electrical and fabrication complexity, making faults even harder to locate. In this work, we used a high-resolution quantum magnetic imaging technique, based on nitrogen-vacancy centers in diamond, to investigate short-circuit faults in an ion trap chip. We imaged currents from these short-circuit faults to ground and compared them to intentionally created faults, finding that the root cause of the faults was failures in the on-chip trench capacitors. This work, where we exploited the performance advantages of a quantum magnetic sensing technique to troubleshoot a piece of quantum computing hardware, is a unique example of the evolving synergy between emerging quantum technologies to achieve capabilities that were previously inaccessible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗