Establishing Quality Metrics for Systems Engineering Process

Abstract

AbstractSoftware engineering companies such as Motorola have clearly defined, robust processes to ensure overall process and system quality. Using Motorola's approach as a baseline, the authors established a process to determine system complexity to support the Systems Engineering & Integration (SE&I) lifecycle. To quantify complexity, the authors established a process including structural complexity (focused on system form), dynamic complexity (focused on system function), and social complexity (focused on identified stakeholders), the sum of which define complexity points. The authors further expanded the process by defining key metrics and parameters to support evaluation throughout the SE&I phases from concept to operationalization. This process, which utilizes fundamentals of Agile Software Development, allows systems engineers (SEs) and program managers (PMs) to quantitatively compare SE&I phases, systems, or projects of different sizes and dollar values to categorize, assess, forecast lifecycle costs, and performance to improve performance with customer satisfaction in mind. Through a satellite system example, the authors present the metrics to support associated analysis through the SE&I lifecycle.