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Integration of System Modeling and Design Processes, Data and Technology for Streamlining Enterprise Integration

机译：集成系统建模和设计过程，数据和技术以简化企业集成

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Complex systems, Pattern-based Systems Engineering, and Model-based Systems Engineering are approaches to model system lifecycles and address engineered systems complexity. Each approach advocates languages, tools, and processes as supplements to traditional engineering processes; however, these approaches are not readily adopted. The challenge for these system modeling approaches is they are not linked to traditional engineering processes and require unique tools and languages independent of traditional engineering domains. Furthermore, the knowledge of the external standards and specifications used in traditional processes are not available to users of system modeling technology, and those who have knowledge of external standards and specifications do not have knowledge of system modeling technology. Moreover, embedding intelligence of external standards and specifications is available within traditional system modeling applications. The research goal is integrating the technology and processes employed by system modeling and traditional engineering to automate data creation, flow and validation through removal of barriers to rule-driven technology adoption. Rule-driven technology adoption should lead to efficiencies in creating and managing extremely large datasets through automation. The results project significant improvement to data quality and enterprise IT systems integration while reducing labor costs to; validate data, avoid and correct errors, and eliminate data omissions.
机译：复杂系统，基于模式的系统工程和基于模型的系统工程是对系统生命周期进行建模并解决工程系统复杂性的方法。每种方法都提倡语言，工具和过程作为对传统工程过程的补充;但是，这些方法并不容易采用。这些系统建模方法面临的挑战是它们不与传统工程流程链接，并且需要独立于传统工程领域的独特工具和语言。此外，传统建模中使用的外部标准和规范的知识对系统建模技术的用户不可用，而具有外部标准和规范的知识的人则不具有系统建模技术的知识。而且，在传统的系统建模应用程序中可以使用外部标准和规范的嵌入智能。研究目标是整合系统建模和传统工程采用的技术和流程，以消除规则驱动技术采用的障碍，从而自动进行数据创建，流程和验证。采用规则驱动的技术应可通过自动化提高创建和管理超大型数据集的效率。结果表明，在降低劳动力成本的同时，可以显着改善数据质量和企业IT系统集成。验证数据，避免和纠正错误，并消除数据遗漏。

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