EAGER: A Systems Approach to Predicting and Preventing Accidents During Operations

这个早期概念探索性研究补助金(AGIRE)项目将通过采取第一个概念验证步骤来调查一种新的方法，以确定在事故发生前发出潜在信号的领先指标，从而为国家的经济繁荣、安全和福祉做出贡献。尽管我们的初衷是开发安全的产品和服务，但事故和损失仍在发生。随着当今我们的先进技术所涉及的更大损失的可能性增加，设计本质上安全的系统将变得更加困难，操作风险管理实践将变得更加重要。重大事故发生前总会有警示信号，但这些征兆可能只有在事后才能察觉和解读。与此同时，现在计算机可以收集大量的数据，但由于这些数据的大小和从数据中创建有用信息的困难，这些数据中的大多数都没有被使用。这项研究将采用一种新的独特方法来分析运营数据，并确定风险何时增加。三家国际航空公司参与了这项研究，他们提供了真实的运营数据和专业知识，以验证新风险分析技术的可行性和有效性。虽然航空公司的运营被用作试验床，但研究成果可以扩展到任何安全关键行业。这项研究要评估的基本假设是，可以根据所采用的安全工程做法所依据的假设以及这些假设的脆弱性来确定有用的领先指标。这一过程将需要使用各种类型的业务数据，这些数据可以(而且经常是)收集，但需要一些过程来确定收集的数据的潜在后果。这项研究将建立一个新的事故因果关系模型STAMP(系统理论事故模型和过程)和一种新的危险分析技术(STPA或系统理论过程分析)来研究该模型。STAMP将当前的事故因果关系扩展到包括更复杂的原因，而不是简单的部件故障和一连串故障事件或偏离操作预期(这是传统危险分析方法的基础)。STAMP融合了系统思维的基本原理，并基于系统理论而不是传统的可靠性理论。将创建一种名为Active STPA的新分析工具，该工具将使用在运营期间通常收集的数据来识别在运营期间违反在产品或服务的设计和开发期间所做的假设，从而可能成为事故的前兆和风险可能增加的证据。试验台将是航空公司的运营。虽然这项研究的主题仅限于确定与安全和事故相关的领先指标，但这些想法将适用于除安全之外的系统属性的领先指标和风险管理，并可能开辟一条新的途径来评估运营期间的风险，供研究人员探索。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This EArly-concept Grant for Exploratory Research (EAGER) project will contribute to the economic prosperity, safety and wellbeing of the nation by taking the first proof-of-concept steps in investigating a new approach to identifying leading indicators signaling the potential for an accident before it occurs. Despite our best intentions to develop safe products and services, accidents and losses still occur. As the potential for greater losses involved in our advanced technology today increases, it will be harder to design inherently safe systems and operational risk management practices will become more important. There are always warning signs before a major accident, but these signs may only be noticeable and interpretable in hindsight. At the same time, enormous amounts of data can now be collected by computers but most of theses data are not used because of the size and difficulty in creating useful information from the data. This research will take a new and unique approach to analyzing operational data and identifying when risk is increasing. Three international airlines are participating in the research by providing real operational data and their expertise to validate the feasibility and efficacy of the new risk analysis technique. While airline operations are used as the testbed, the research results can be extended to any safety-critical industry. The basic hypothesis to be evaluated in this research is that useful leading indicators can be identified based on the assumptions underlying the safety engineering practices employed and on the vulnerability of those assumptions. This process will require the use of various types of operational data that can be (and often is) collected but needs some process for determining the potential consequences of the collected data. The research will build on a new model of accident causation called STAMP (System-Theoretic Accident Model and Processes) and a new hazard analysis technique (STPA or System-Theoretic Process Analysis) to work on that model. STAMP extends current accident causality to include more complex causes than simply component failures and chains of failure events or deviations from operational expectations (which is the basis for traditional hazard analysis methods). STAMP incorporates basic principles of systems thinking and is based on systems theory rather than traditional reliability theory. A new analysis tool called Active STPA will be created that will use data commonly collected during operations to identify when the assumptions made during design and development of a product or service are violated during operations and thus may be a precursor for an accident and evidence that risk may be increasing. The test bed will be airline operations. While the subject of this research is limited to identifying leading indicators related to safety and accidents, the ideas will apply to leading indicators and risk management for system properties other than safety and could open a new path to evaluating risk during operations for researchers to exploreThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.