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Project

Optimization design of additive manufacturing structures under uncertainty

Additive manufacturing (AM) refers to the use of layer-based additive processes to manufacture finished parts by stacking layers of thin two-dimensional (2D) cross-sectional slices of materials. In some of the leading application areas such as aerospace, biomedical, and automotive, AM has demonstrated unprecedented flexibility for part consolidation, function integration, and lightweight of structure and component designs. Apart from the superior mechanical performances, various sources of uncertainty, such as modeling assumptions, numerical approximation, input parameters, and measurement error are involved in the AM processes, which result in variability in the quality of the manufactured component. The quality variation hinders the consistent manufacturing of products with guaranteed high quality. This becomes a major hurdle for the wide application of AM techniques. The objective of the research is to establish the process-structure-property relationship based on the needs of properties or responses and further improve the performance and reliability of AM components with the development of numerical methods for the design of AM structures accounting for uncertainty sources in each step of the AM process and their effects on product quality. Moreover, based on the proposed design and optimization approach, intriguing AM components will be fabricated and tested under various practical engineering scenarios to verify the effectiveness and merits of proposed framework. The whole research is divided into four main tasks including: modeling of uncertainty sources, uncertainty quantification (UQ) in AM, topology design of AM structures under uncertainty, and test of fabricated AM structures.

Date:19 Apr 2022 →  Today
Keywords:Additive manufacturing
Disciplines:Manufacturing processes, methods and technologies
Project type:PhD project