Modelling Methodologies for Quality Assessment of 3D Inkjet Printed Electronic Products

摘要

Achieving optimal performance, quality and reliability is a key factor for the success and adoption of 3D printing technology in electronics manufacturing applications. This paper presents modelling methodologies and toolsets that can help in addressing these 3D inkjet printing process challenges. The main discussions are on (1) Modelling the structural behaviour of typical printed electronics structures using finite element analysis and (2) Condition based monitoring (CBM) for product quality/performance using machine learning techniques. Advanced capabilities in finite element modelling and data-driven techniques are employed in order to enable the assessment of the material behaviour of the ink-based materials during printing and in their post-cure state. Demonstrations of the modelling capabilities with respect to both approaches are given with representative study cases. Results show that layer-by-layer build up can lead to structural weakness and dimensional inaccuracy in the third dimension due to cure shrinkage. Model predictions offer quantitative analysis of the cure shrinkage effects and can inform on optimal material selection and process conditions. Data from measurements and sensors can enable diagnostics and prognostics predictions and thus help achieving product specification requirements.