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Reduction of Railway System Failures through Technical Uncertainty Analysis Open Access

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Since the opening of the Washington Metropolitan Transit Authority (WMATA) in 1976, failures have negatively affected consistent railway service across the areas. Over the last three years, WMATA has attempted increase efforts to perform critical maintenance that would increase performance and reliability of railway services. The cost to the agency and impacts to ridership, along with the growing population, has created barriers to improve the quality within such a large-scale, complex system. But the amount of uncertainty in technical decisions seems to have large impacts on the abilities of engineers, technologist, and decision makers to reduce failures. Uncertainty is an attribute of probabilistic logic that diminishes the ability to leverage deductive reasoning for decision makers. Many systems engineers rely heavily on risk analysis to manage potential system failures. Although not readily quantified, the quantity of uncertainty within technical risks embodies the lack of predictability of system outcomes and, in most cases, lead to failures. Recent research loosely describes the impacts of uncertainties on solution development within large-scale, complex systems. In addition, there is a lack of rigor and application of formal system analysis concepts to accurately identify and control uncertainty within systems across multiple industries and sectors. The research of technical uncertainty within large-scale, complex systems provides critical insight in determining the appropriate decisions for failure reduction. Unfortunately, the dimensionality0F0F within larger systems increases the complexity of accurately predicting the system outcomes and their ability to meet stakeholder’s needs. Dimensionality is typically a negligible characteristic within small, less complex systems. But as the number of variables grow within the system, the inability to quantify uncertainty results in increase risks and unavoidable failures. The quantification of uncertainty within technical systems, defined as technical uncertainties , could be used to optimize how engineers and technologists plan, architect, design, implement, and support more complex systems integration efforts with a focus on failure reduction. This research establishes a technical uncertainty framework and quantification methodology to reduce system failures and increase reliability within a metropolitan railway system using disruption data from the Washington Metropolitan Transit Authority (WMATA).

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