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

Abstract

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.