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Development of a Data Management Methodology for a Commercial-Off-The-Shelf (COTS) Part-Testing Program to Meet the Needs of a Broad Range of Users (304239)

Lee A Crowder, Sandia National Laboratories 
Stephen C Hwang, Sandia National Laboratories 
*Christopher L Stork, Sandia National Laboratories 

Keywords: Data management, data engineering, commercial-off-the-shelf (COTS) parts, metadata, surveillance, qualification

In support of an electronic commercial-off-the-shelf (COTS) part testing, surveillance, and qualification program, Sandia National Labs collects large volumes of information, including manufacturing data, metadata specifying part environmental exposure and test conditions, and electrical test data. Multiple user groups, namely engineers designing testing protocols and qualifying parts, technologists performing testing, statistical analysts tasked with extracting relevant trends, and management/customers requiring high-level metrics, must leverage COTS data to make timely technical and business decisions. COTS part testing data have been stored in disparate locations in an unorganized format, making it difficult to use these data to answer questions from a broad range of users. In this introductory-level presentation, we highlight a data management approach, specifically the organization of the COTS program data into distinct, linkable data tables (part manufacturing information, part tracking information, part processing information, electrical test data, test information), designed to provide improved analytics and streamline the process by which user questions can be answered.