Record Details

International Space Station (ISS) Anomalies Trending Study
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Author and Affiliation:
Beil, Robert J.(NASA Langley Research Center, Hampton, VA, United States);
Brady, Timothy K.(NASA Langley Research Center, Hampton, VA, United States);
Foster, Delmar C.(Data Mining USA, Kennedy Space Center, FL, United States);
Graber, Robert R.(Science Applications International Corp., Houston, TX, United States);
Malin, Jane T.(NASA Johnson Space Center, Houston, TX, United States);
Thornesbery, Carroll G.(S and K Aerospace, Inc., Saint Ignatius, MT, United States);
Throop, David R.(Jacobs Technology, Inc., Houston, TX, United States)
Abstract: The NASA Engineering and Safety Center (NESC) set out to utilize data mining and trending techniques to review the anomaly history of the International Space Station (ISS) and provide tools for discipline experts not involved with the ISS Program to search anomaly data to aid in identification of areas that may warrant further investigation. Additionally, the assessment team aimed to develop an approach and skillset for integrating data sets, with the intent of providing an enriched data set for discipline experts to investigate that is easier to navigate, particularly in light of ISS aging and the plan to extend its life into the late 2020s. This report contains the outcome of the NESC Assessment.
Publication Date: Sep 24, 2015
Document ID:
20160001621
(Acquired Feb 08, 2016)
Subject Category: MATHEMATICAL AND COMPUTER SCIENCES (GENERAL)
Report/Patent Number: NASA/TM-2015-218991 Vol. 1, NESC-RP-14-00950, L-20648, NF1676L-23240
Document Type: Technical Report
Contract/Grant/Task Num: WBS 869021.01.07.01.01
Financial Sponsor: NASA Langley Research Center; Hampton, VA, United States
Organization Source: NASA Langley Research Center; Hampton, VA, United States
Description: 53p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Distribution as joint owner in the copyright
NASA Terms: INTERNATIONAL SPACE STATION; ANOMALIES; DATA MINING; TREND ANALYSIS; DATA BASES; COMPUTER PROGRAMS; SOFTWARE DEVELOPMENT TOOLS; HUMAN FACTORS ENGINEERING; HAZARDS; FAILURE MODES; REPORTS; LESSONS LEARNED
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