TPS指标提取软件的资源管理

J. Luna, M. Morgan, C. Geiger
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引用次数: 0

摘要

美国海军拥有大量测试程序集(TPS)代码和相关数据,这是自动测试系统(ATS)规划和支持中尚未开发的资源。将测试仪器能力与TPS源数据和ATS使用数据联系起来的能力,将为航空电子设备的维护提供一个全面的视角。这可以确定部署新的和创新的测试技术的机会的经济目标。目前还没有技术可以利用可用的TPS代码和相关数据。这项工作的目标是开发一个软件工具集,该工具集提供了从TPS源代码和ATS日志数据中提取使用指标的创新功能。本文描述了一项致力于定义和开发用于ATE和TPS数据聚合和分析的完整数据度量生成概念的工作。这是一项新功能,可以解析TPS源代码并提取利用其他数据源(如日志数据和UUT维护数据)的度量。该过程的结果是创建可用于支持使用分析的TPS和ATS组件使用度量。作为这项工作的结果,从TPS源代码和TPS日志文件中提取和分析指标的概念软件得到了成功的演示。该能力的一个关键目标是展示武器可替换组件(WRA)和子系统可替换组件(SRA)测试的标准海军维护数据如何与TPS数据合并,以确定企业利用率和基于预测维护需求数据的未来利用率预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TPS metrics extraction software for resource management
The Navy has a large set of Test Program Set (TPS) code and associated data that are an untapped resource in Automatic Test System (ATS) planning and support. The ability to relate test instrument capabilities to TPS source data and ATS usage data would provide a comprehensive look at how avionics maintenance is performed. This could identify economic targets of opportunity for the deployment of new and innovative test techniques. Currently the technology does not exist to tap into the available TPS code and associated data. The objective of this effort was to develop a software toolset that provides an innovative capability to extract usage metrics from TPS source code and ATS log data. This paper describes an effort focused on defining and developing a complete data metrics generation concept for the aggregation and analysis of ATE and TPS data. This is a new capability that parses TPS source code and extract metrics that leverages other sources of data, such as log data and UUT maintenance data. The result of the process is the creation of TPS and ATS component usage metrics that can be used to support usage analyses. As a result of this effort, concept software for metrics extraction and analysis from TPS source code and TPS log files was successfully demonstrated. A key goal of this capability is to show how standard Navy maintenance data for Weapon Replaceable Assembly (WRA) and Subsystem Replaceable Assembly (SRA) testing can be merged with TPS data to determine enterprise utilization and prediction of future utilization based on predicted maintenance demand data.
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