{"title":"法医数据和决策:利用数据用于其他目的","authors":"D. Wisch, L. Huyse","doi":"10.4043/29601-MS","DOIUrl":null,"url":null,"abstract":"\n During installation of the Big Foot TLP, nine of the 16 pre-installed tendons fell to the seafloor prior to completion of installation. a comprehensive Root Cause Analysis was undertaken to determine the \"cause\" of the incident. During the early investigative phase, a number of sources of data were identified. Two particular information sets were gathered, interrogated, processed, etc. to extract usable patterns and values to aid in decision making. A third composite data set of deepwater current values was coupled to extract additional insights. All data sets were designed for installation support and not intended for a forensic investigation. Identification of the data, understanding original intent, multi-stage filtering and conclusions will be illustrated.\n One is a time series containing x, y, z spatial data of a common location on each of the 16 pre-installed tendon assemblies and the second being non-periodic discrete air volume measurements of buoyancy devices. The time series data contained repetitive data points, contained spurious readings, etc. The multi-stage automatic and manual filtering processes utilized to develop non-periodic traces useful for insight and decision making is described. Accompanying this discussion will be the description of original intent and the adaptation from intended use to RCA value. The second data involved non-periodic air volume measurements. Initial interpretation of data during installation was sufficient for operational purposes. A Root Cause Analysis team analyzed the data including use of correlative time series unrelated to the measurement to identify telling patterns useful in decisions.\n The absolute as recorded data was unable to provide sufficient confidence using standard data processing techniques. Target manual filtering and correlative comparisons provided useful and valuable decision-making insights. The ability to use data designed for specific purposes not aligned with ultimate usage for RCA purposes is shown","PeriodicalId":11149,"journal":{"name":"Day 1 Mon, May 06, 2019","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forensic Data & Decisions: Utilizing Data Intended for Other Purposes\",\"authors\":\"D. Wisch, L. 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Identification of the data, understanding original intent, multi-stage filtering and conclusions will be illustrated.\\n One is a time series containing x, y, z spatial data of a common location on each of the 16 pre-installed tendon assemblies and the second being non-periodic discrete air volume measurements of buoyancy devices. The time series data contained repetitive data points, contained spurious readings, etc. The multi-stage automatic and manual filtering processes utilized to develop non-periodic traces useful for insight and decision making is described. Accompanying this discussion will be the description of original intent and the adaptation from intended use to RCA value. The second data involved non-periodic air volume measurements. Initial interpretation of data during installation was sufficient for operational purposes. A Root Cause Analysis team analyzed the data including use of correlative time series unrelated to the measurement to identify telling patterns useful in decisions.\\n The absolute as recorded data was unable to provide sufficient confidence using standard data processing techniques. Target manual filtering and correlative comparisons provided useful and valuable decision-making insights. 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引用次数: 0
摘要
在大脚张力腿平台的安装过程中,16根预安装的肌腱中有9根在安装完成之前就掉到了海底。进行了全面的根本原因分析,以确定事件的“原因”。在早期调查阶段,确定了一些数据来源。收集、询问、处理两个特定的信息集,以提取可用的模式和值来帮助决策。第三个复合数据集结合了深水电流值,以获得更多的见解。所有数据集都是为安装支持而设计的,并非用于取证调查。将说明数据的识别、理解原始意图、多阶段过滤和结论。一个是包含16个预安装的肌腱组件上每个共同位置的x, y, z空间数据的时间序列,第二个是浮力装置的非周期性离散空气体积测量。时间序列数据包含重复的数据点,包含虚假读数等。描述了用于开发对洞察力和决策有用的非周期性跟踪的多阶段自动和手动过滤过程。伴随此讨论的将是对原始意图的描述以及从预期用途到RCA价值的调整。第二个数据涉及非周期性空气量测量。安装期间对数据的初步解释足以用于操作目的。根本原因分析团队分析数据,包括使用与测量无关的相关时间序列,以确定对决策有用的告诉模式。使用标准数据处理技术,绝对记录的数据无法提供足够的信心。目标人工过滤和相关比较提供了有用和有价值的决策见解。显示了为特定目的而设计的数据与RCA目的的最终用途不一致的能力
Forensic Data & Decisions: Utilizing Data Intended for Other Purposes
During installation of the Big Foot TLP, nine of the 16 pre-installed tendons fell to the seafloor prior to completion of installation. a comprehensive Root Cause Analysis was undertaken to determine the "cause" of the incident. During the early investigative phase, a number of sources of data were identified. Two particular information sets were gathered, interrogated, processed, etc. to extract usable patterns and values to aid in decision making. A third composite data set of deepwater current values was coupled to extract additional insights. All data sets were designed for installation support and not intended for a forensic investigation. Identification of the data, understanding original intent, multi-stage filtering and conclusions will be illustrated.
One is a time series containing x, y, z spatial data of a common location on each of the 16 pre-installed tendon assemblies and the second being non-periodic discrete air volume measurements of buoyancy devices. The time series data contained repetitive data points, contained spurious readings, etc. The multi-stage automatic and manual filtering processes utilized to develop non-periodic traces useful for insight and decision making is described. Accompanying this discussion will be the description of original intent and the adaptation from intended use to RCA value. The second data involved non-periodic air volume measurements. Initial interpretation of data during installation was sufficient for operational purposes. A Root Cause Analysis team analyzed the data including use of correlative time series unrelated to the measurement to identify telling patterns useful in decisions.
The absolute as recorded data was unable to provide sufficient confidence using standard data processing techniques. Target manual filtering and correlative comparisons provided useful and valuable decision-making insights. The ability to use data designed for specific purposes not aligned with ultimate usage for RCA purposes is shown