Literature Review of Short-term production planning for Additive Manufacturing (3D printing)

Literature review of short-term production planning for Additive Manufacturing (3D printing) Abstract This thesis presents a literature review to explore the challenges of scheduling in Additive manufacturing (AM) focusing on innovative scheduling methodologies to tackle the unique challenges of AM processes. Scheduling in (AM) faces challenges such as material and process selection, part geometries, integration with existing systems, customization demands, material availability, which traditional scheduling methods often fail to resolve. Through literature review, optimization strategies and domain expertise papers, thesis shows novel scheduling strategies designed to enhance key performance metrics like lead time, throughput, and energy consumption. The thesis reviewed numerous papers on short term production planning of AM, the state-of-the-art methodologies found in the literature review include principles from optimization and operations, integrating automation, robotics, and AI to streamline AM production planning. Conclusive literature review remarks suggest that these adaptive scheduling strategies requires advanced scheduling algorithms, real-time monitoring, and seamless integration of automation and robotics to ensure efficient, high-quality production, improve productivity, reduce costs, and accelerate time to market for AM-produced components. By advancing efficient scheduling methodologies, the thesis aims to support Additive Manufacturing (AM)’s broader integration into mainstream manufacturing.