Thesis

An integrated process-structure-property-performance modelling framework for additive layer manufacturing of Ti-6Al-4V

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Awarding institution
  • University of Strathclyde
Date of award
  • 2026
Thesis identifier
  • T18105
Person Identifier (Local)
  • 202163274
Qualification Level
Qualification Name
Department, School or Faculty
Abstract
  • Additive Manufacturing is proving to be a revolutionary manufacturing process that is making its way into all engineering industries that require high-performance and light-weight structural components. This is mainly thanks to its ability to manufacture complex shapes that are unobtainable by conventional processes, which allows designers to be freed from manufacturing constraints and produce previously unmanufacturable components with unprecedented capabilities. Nonetheless, the fast adoption of additive manufacturing is hindered by poor or inconsistent material performance that is highly dependent on a component’s shape and manufacturing parameters. Computational models that establish relationships between geometry, process parameters, and performance offer a valuable solution to overcome this challenge. Such models can predict potential performance issues and guide the selection of optimal manufacturing parameters to prevent them. Nevertheless, developing these models is a complex task due to the intricate physics involved at different scales that impact the mechanical properties of an additively manufactured metal. This Ph.D. thesis proposes a multi-physics and multi-scale modelling approach to fully digitally correlate the process parameters of selective laser melted Ti-6Al-4V with its elasto-plastic mechanical properties and structural performance. The method involves coupling micro-scale crystal plasticity simulations to calculate mechanical properties with a component-scale thermal process model through a mean-field microstructure evolution model. The developed automated modelling tool could be used in optimisation of process parameters and geometrical design to achieve peak performance in additively manufactured structural components. Furthermore, a rigorous analysis of the developed model is presented with comprehensive experimental validation. Overall, the proposed Process-Structure-Property-Performance framework demonstrated a strong foundation for improving the predictive accuracy of digital structural analysis of additively manufactured components. However, several limitations were appreciated. The high computational cost of the thermal process model restricts its practicality for iterative optimisation frameworks, while the absence of damage and distortion modelling constrains its predictive scope. Addressing these challenges will be essential to extend the applicability of the framework and enable its integration into robust, industry-ready digital design and optimisation workflows.
Advisor / supervisor
  • Rahimi, Salaheddin
  • Huang, Jianglin
Resource Type
DOI
Date Created
  • 2025
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