Optimizing additive manufacturing workflows using model-based systems engineering

Abstract

• ASAM streamlines AM workflows using MBSE for better efficiency. • CESAM and SysML ensure compliance and enhance design validation. • ASAM detects flaws and optimizes 3D models for printability. • Aligns user needs with functions for a flexible 3D printing tool. • Reduces waste, shortens lead time, and improves AM quality. . Additive Manufacturing (AM) is a transformative technology enabling the production of complex geometries with reduced waste and lead times. However, optimizing AM workflows involves addressing challenges such as design validation, process parameters, and compliance with industry standards. In this paper, a Model-Based Systems Engineering (MBSE) approach is proposed to support the conceptual design of the Advisor System for Additive Manufacturing (ASAM), a framework aimed at streamlining AM workflows. The ASAM framework utilizes the CESAM architecture and System Modelling Language (SysML) to create multi-architecture models of the AM process, integrating operational, functional, and constructional perspectives. These models formalize the system architecture, providing a foundation for developing automated design validation, flaw detection, and optimization mechanisms. Future iterations of ASAM will incorporate advanced algorithms for real-time parameter optimization and predictive analytics. To demonstrate the feasibility of the proposed approach, the initial phase focuses on conceptual modelling and scalability assessment. Illustrative scenarios across aerospace, healthcare, and education industries are used to evaluate the adaptability and potential impact of the framework. The results highlight ASAM's capability to formalize AM workflow architectures and lay the groundwork for improved efficiency, compliance, and scalability in future implementations.