Special Issue on Uncertainty Quantification and Management in Additive Manufacturing

Abstract

Additive manufacturing (AM) represents a new paradigm of manufacturing where parts are manufactured using their 3D models (such as CAD models) by joining materials in a layer-by-layer manner. Widespread implementation of additive manufacturing requires robust techniques for performance evaluation, quality control, and certification. AM product quality is impacted by multiple uncertainty sources that are present at various stages of the manufacturing process, such as raw materials, process equipment, process parameters, process simulation models, and sensor measurements. Therefore, techniques of uncertainty quantification and management (UQ&amp

M) are essential for the quality control and certification of additive manufacturing processes. With the development of advanced simulation techniques, artificial intelligence, and big data analytics, new UQ&amp

M approaches are emerging to enable model-based quality control and certification, data-driven quality monitoring, and AI-based quality assurance in additive manufacturing. This special issue covers various recent advances in the field of UQ&amp

M with a focus on additive manufacturing.