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All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Apollo experience report: Problem reporting and corrective action system

The Apollo spacecraft Problem Reporting and Corrective Action System is presented. The evolution from the early system to the present day system is described. The deficiencies and the actions taken to correct them are noted, as are management controls for both the contractor and NASA. Significant experience gained from the Apollo Problem Reporting and Corrective Action System that may be applicable to future manned spacecraft is presented.

Adams, T. J.↗
NASA NTRS2016

Topic Modeling of NASA Space System Problem Reports: Research in Practice

Problem reports at NASA are similar to bug reports: they capture defects found during test, post-launch operational anomalies, and document the investigation and corrective action of the issue. These artifacts are a rich source of lessons learned for NASA, but are expensive to analyze since problem reports are comprised primarily of natural language text. We apply topic modeling to a corpus of NASA problem reports to extract trends in testing and operational failures. We collected 16,669 problem reports from six NASA space flight missions and applied Latent Dirichlet Allocation topic modeling to the document corpus. We analyze the most popular topics within and across missions, and how popular topics changed over the lifetime of a mission. We find that hardware material and flight software issues are common during the integration and testing phase, while ground station software and equipment issues are more common during the operations phase. We identify a number of challenges in topic modeling for trend analysis: 1) that the process of selecting the topic modeling parameters lacks definitive guidance, 2) defining semantically-meaningful topic labels requires nontrivial effort and domain expertise, 3) topic models derived from the combined corpus of the six missions were biased toward the larger missions, and 4) topics must be semantically distinct as well as cohesive to be useful. Nonetheless,topic modeling can identify problem themes within missions and across mission lifetimes, providing useful feedback to engineers and project managers.

Data Mining↗
NASA NTRS2008

Problem Reporting System

The Problem Reporting System (PRS) is a Web application, running on two Web servers (load-balanced) and two database servers (RAID-5), which establishes a system for submission, editing, and sharing of reports to manage risk assessment of anomalies identified in NASA's flight projects. PRS consolidates diverse anomaly-reporting systems, maintains a rich database set, and incorporates a robust engine, which allows tracking of any hardware, software, or paper process by configuring an appropriate life cycle. Global and specific project administration and setup tools allow lifecycle tailoring, along with customizable controls for user, e-mail, notifications, and more. PRS is accessible via the World Wide Web for authorized user at most any location. Upon successful log-in, the user receives a customizable window, which displays time-critical 'To Do' items (anomalies requiring the user s input before the system moves the anomaly to the next phase of the lifecycle), anomalies originated by the user, anomalies the user has addressed, and custom queries that can be saved for future use. Access controls exist depending on a user's role as system administrator, project administrator, user, or developer, and then, further by association with user, project, subsystem, company, or item with provisions for business-to-business exclusions, limitations on access according to the covert or overt nature of a given project, all with multiple layers of filtration, as needed. Reporting of metrics is built in. There is a provision for proxy access (in which the user may choose to grant one or more other users to view screens and perform actions as though they were the user, during any part of a tracking life cycle - especially useful during tight build schedules and vacations to keep things moving). The system also provides users the ability to have an anomaly link to or notify other systems, including QA Inspection Reports, Safety, GIDEP (Government-Industry Data Exchange Program) Alert, Corrective Actions, and Lessons Learned. The PRS tracking engine was designed as a very extensible and scalable system, able to support additional applications, with future development possibilities already discussed, including Incident Surprise Anomalies (for anomalies occurring during Operations phases of NASA Flight projects), GIDEP and NASA Alerts, and others.

Potter, Don↗
NASA NTRS2013

Determining Component Probability using Problem Report Data for Ground Systems used in Manned Space Flight

During the shuttle era NASA utilized a failure reporting system called the Problem Reporting and Corrective Action (PRACA) it purpose was to identify and track system non-conformance. The PRACA system over the years evolved from a relatively nominal way to identify system problems to a very complex tracking and report generating data base. The PRACA system became the primary method to categorize any and all anomalies from corrosion to catastrophic failure. The systems documented in the PRACA system range from flight hardware to ground or facility support equipment. While the PRACA system is complex, it does possess all the failure modes, times of occurrence, length of system delay, parts repaired or replaced, and corrective action performed. The difficulty is mining the data then to utilize that data in order to estimate component, Line Replaceable Unit (LRU), and system reliability analysis metrics. In this paper, we identify a methodology to categorize qualitative data from the ground system PRACA data base for common ground or facility support equipment. Then utilizing a heuristic developed for review of the PRACA data determine what reports identify a credible failure. These data are the used to determine inter-arrival times to perform an estimation of a metric for repairable component-or LRU reliability. This analysis is used to determine failure modes of the equipment, determine the probability of the component failure mode, and support various quantitative differing techniques for performing repairable system analysis. The result is that an effective and concise estimate of components used in manned space flight operations. The advantage is the components or LRU's are evaluated in the same environment and condition that occurs during the launch process.

Monaghan, Mark W.↗
NASA NTRS2011

Semantic Annotation of Complex Text Structures in Problem Reports

Text analysis is important for effective information retrieval from databases where the critical information is embedded in text fields. Aerospace safety depends on effective retrieval of relevant and related problem reports for the purpose of trend analysis. The complex text syntax in problem descriptions has limited statistical text mining of problem reports. The presentation describes an intelligent tagging approach that applies syntactic and then semantic analysis to overcome this problem. The tags identify types of problems and equipment that are embedded in the text descriptions. The power of these tags is illustrated in a faceted searching and browsing interface for problem report trending that combines automatically generated tags with database code fields and temporal information.

Malin, Jane T.↗
NASA NTRS1993

Problem reporting management system performance simulation

This paper proposes the Problem Reporting Management System (PRMS) model as an effective discrete simulation tool that determines the risks involved during the development phase of a Trouble Tracking Reporting Data Base replacement system. The model considers the type of equipment and networks which will be used in the replacement system as well as varying user loads, size of the database, and expected operational availability. The paper discusses the dynamics, stability, and application of the PRMS and addresses suggested concepts to enhance the service performance and enrich them.

Vannatta, David S.↗
NASA NTRS2010

Problem Reporting Taxonomy and Data Preparation Tool Evaluation

A member of the NASA Engineering and Safety Center (NESC) Systems Engineering Office (SEO) Technical Discipline Team (TDT) requested a SEO-managed activity to perform a gap analysis on the proposed NASA Standard 0006, "Common NASA Taxonomy for Problem Reporting, Analysis, and Resolution", and to create an input filter and set of instructions for using the data-mining/data-cleansing tool TechOasis1 with Space Shuttle Program (SSP) problem reporting data. The work that achieved these objectives and deployment of TechOasis are discussed in this report.

Beil, Robert J.↗
NASA NTRS2006

Enabling the Discovery of Recurring Anomalies in Aerospace System Problem Reports using High-Dimensional Clustering Techniques

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0-

Srivastava, Ashok, N.↗
NASA NTRS1995

Structural Damage Prediction and Analysis for Hypervelocity Impact. BUMPERII Suggestion and Problem Reports

In the course of preparing the SD_SURF space debris analysis code, several problems and possibilities for improvement of the BUMPERII code were documented and sent to MSFC. These suggestions and problem reports are included here as a part of the contract final report. This includes reducing BUMPERII memory requirements, compiling problems with BUMPERII, FORTRAN-lint analysis of BUMPERII, and error in function PRV in BUMPERII.

Source record↗
NASA NTRS2009

Lessons Learned for Cx PRACA. Constellation Program Problem Reporting, Analysis and Corrective Action Process and System

This slide presentation reviews the Constellation Program Problem Reporting, Analysis and Corrective Action Process and System (Cx PRACA). The goal of the Cx PRACA is to incorporate Lessons learned from the Shuttle, ISS, and Orbiter programs by creating a single tool for managing the PRACA process, that clearly defines the scope of PRACA applicability and what must be reported, and defines the ownership and responsibility for managing the PRACA process including disposition approval authority. CxP PRACA is a process, supported by a single information gathering data module which will be integrated with a single CxP Information System, providing interoperability, import and export capability making the CxP PRACA a more effective and user friendly technical and management tool.

Kelle, Pido I.↗
NASA NTRS2006

NASA Taxonomies for Searching Problem Reports and FMEAs

Many types of hazard and risk analyses are used during the life cycle of complex systems, including Failure Modes and Effects Analysis (FMEA), Hazard Analysis, Fault Tree and Event Tree Analysis, Probabilistic Risk Assessment, Reliability Analysis and analysis of Problem Reporting and Corrective Action (PRACA) databases. The success of these methods depends on the availability of input data and the analysts knowledge. Standard nomenclature can increase the reusability of hazard, risk and problem data. When nomenclature in the source texts is not standard, taxonomies with mapping words (sets of rough synonyms) can be combined with semantic search to identify items and tag them with metadata based on a rich standard nomenclature. Semantic search uses word meanings in the context of parsed phrases to find matches. The NASA taxonomies provide the word meanings. Spacecraft taxonomies and ontologies (generalization hierarchies with attributes and relationships, based on terms meanings) are being developed for types of subsystems, functions, entities, hazards and failures. The ontologies are broad and general, covering hardware, software and human systems. Semantic search of Space Station texts was used to validate and extend the taxonomies. The taxonomies have also been used to extract system connectivity (interaction) models and functions from requirements text. Now the Reconciler semantic search tool and the taxonomies are being applied to improve search in the Space Shuttle PRACA database, to discover recurring patterns of failure. Usual methods of string search and keyword search fall short because the entries are terse and have numerous shortcuts (irregular abbreviations, nonstandard acronyms, cryptic codes) and modifier words cannot be used in sentence context to refine the search. The limited and fixed FMEA categories associated with the entries do not make the fine distinctions needed in the search. The approach assigns PRACA report titles to problem classes in the taxonomy. Each ontology class includes mapping words - near-synonyms naming different manifestations of that problem class. The mapping words for Problems, Entities and Functions are converted to a canonical form plus any of a small set of modifier words (e.g. non-uniformity NOT + UNIFORM.) The report titles are parsed as sentences if possible, or treated as a flat sequence of word tokens if parsing fails. When canonical forms in the title match mapping words, the PRACA entry is associated with the corresponding Problem, Entity or Function in the ontology. The user can search for types of failures associated with types of equipment, clustering by type of problem (e.g., all bearings found with problems of being uneven: rough, irregular, gritty ). The results could also be used for tagging PRACA report entries with rich metadata. This approach could also be applied to searching and tagging failure modes, failure effects and mitigations in FMEAs. In the pilot work, parsing 52K+ truncated titles (the test cases that were available), has resulted in identification of both a type of equipment and type of problem in about 75% of the cases. The results are displayed in a manner analogous to Google search results. The effort has also led to the enrichment of the taxonomy, adding some new categories and many new mapping words. Further work would make enhancements that have been identified for improving the clustering and further reducing the false alarm rate. (In searching for recurring problems, good clustering is more important than reducing false alarms). Searching complete PRACA reports should lead to immediate improvement.

Malin, Jane T.↗
NASA NTRS2001

Assessment of the NASA Space Shuttle Program's Problem Reporting and Corrective Action System

This paper documents the general findings and recommendations of the Design for Safety Programs Study of the Space Shuttle Programs (SSP) Problem Reporting and Corrective Action (PRACA) System. The goals of this Study were: to evaluate and quantify the technical aspects of the SSP's PRACA systems, and to recommend enhancements addressing specific deficiencies in preparation for future system upgrades. The Study determined that the extant SSP PRACA systems accomplished a project level support capability through the use of a large pool of domain experts and a variety of distributed formal and informal database systems. This operational model is vulnerable to staff turnover and loss of the vast corporate knowledge that is not currently being captured by the PRACA system. A need for a Program-level PRACA system providing improved insight, unification, knowledge capture, and collaborative tools was defined in this study.

Korsmeryer, D. J.↗
NASA NTRS1988

Requirements for significant problem reporting and trend analysis

This handbook supplements policies, requirements, and procedures of NMI 8070.3 to ensure that NASA management at each organizational level is: fully aware of trends affecting both the level of safety and the potential for mission success established for both NASA manned space programs and its supporting institutions; fully and independently informed of problems that represent significant risk to the safety of all personnel (including the general populace) and to the success of a mission or operation through a program mechanism herein defined as Significant Problem Reporting; and in full agreement with the level of elimination of these problems through the closed-loop accounting of corrective actions. The requirements of this handbook are supportive of the agency's safety, reliability, maintainability, and quality assurance (SRM&QA) program objectives and are applicable to all organizational elements of NASA connected with or supporting developmental or operational manned space program/projects (including associated payloads) and the related institutional facilities.

George A Rodney↗
NASA NTRS2011

Component-Level Electronic-Assembly Repair (CLEAR) Analysis of the Problem Reporting and Corrective Action (PRACA) Database of the International Space Station On-Orbit Electrical Systems

The NASA Constellation Program is investigating and developing technologies to support human exploration of the Moon and Mars. The Component-Level Electronic-Assembly Repair (CLEAR) task is part of the Supportability Project managed by the Exploration Technology Development Program. CLEAR is aimed at enabling a flight crew to diagnose and repair electronic circuits in space yet minimize logistics spares, equipment, and crew time and training. For insight into actual space repair needs, in early 2008 the project examined the operational experience of the International Space Station (ISS) program. CLEAR examined the ISS on-orbit Problem Reporting and Corrective Action database for electrical and electronic system problems. The ISS has higher than predicted reliability yet, as expected, it has persistent problems. A goal was to identify which on-orbit electrical problems could be resolved by a component-level replacement. A further goal was to identify problems that could benefit from the additional diagnostic and test capability that a component-level repair capability could provide. The study indicated that many problems stem from a small set of root causes that also represent distinct component problems. The study also determined that there are certain recurring problems where the current telemetry instrumentation and built-in tests are unable to completely resolve the problem. As a result, the root cause is listed as unknown. Overall, roughly 42 percent of on-orbit electrical problems on ISS could be addressed with a component-level repair. Furthermore, 63 percent of on-orbit electrical problems on ISS could benefit from additional external diagnostic and test capability. These results indicate that in situ component-level repair in combination with diagnostic and test capability can be expected to increase system availability and reduce logistics. The CLEAR approach can increase the flight crew s ability to act decisively to resolve problems while reducing dependency on Earth-supplied logistics for future Constellation Program missions.

Oeftering, Richard C.↗
NASA NTRS2012

Linguistic Preprocessing and Tagging for Problem Report Trend Analysis

Mr. Robert Beil, Systems Engineer at Kennedy Space Center (KSC), requested the NASA Engineering and Safety Center (NESC) develop a prototype tool suite that combines complementary software technology used at Johnson Space Center (JSC) and KSC for problem report preprocessing and semantic tag extraction, to improve input to data mining and trend analysis. This document contains the outcome of the assessment and the Findings, Observations and NESC Recommendations.

Beil, Robert J.↗
NASA NTRS1989

Lessons learned from trend analysis of Shuttle Payload Processing problem reports

In the wake of the Challenger accident, NASA has placed an increasing emphasis on trend analysis techniques. These analyses provide meaningful insights into system and hardware status, and also develop additional lessons learned from historical data to aid in the design and operation of future space systems. This paper presents selected results from such a trend analysis study that was conducted on the problem report data files for the Shuttle Payload Processing activities. Specifically, the results shown are for the payload canister system which interfaces with and transfers payloads from their processing facilities to the orbiter.

Heuser, Robert E.↗
NASA NTRS1984

Intercenter Problem Reporting and Corrective Action System (PRACAS)

The Kennedy Space Center is transforming the PRACA bath automatic data processing (ADP) system of today into a fully integrated data base with on-line update and retrieval capabilities. The present manual system of reporting (Datafax, mail, and telephone) to the off-site design and engineering organizations is to be replaced by direct access to the most current information as it accrues at KSC or VAFB. Two major goals of the Intercenter PRACA are to provide a single data depository for both launch sites and to fully integrate the problem data with engineering data as well as other relevant information. The resulting ADP system can provide a closed loop system for problem reporting, corrective action and recurrence control that should serve the engineering community as well as reliability and quality assurance at the launch sites, KSC and VAFB, and at the design centers, JSC and MSFC.

Brock, G. H.↗