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
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Qualification Name
Department, School or Faculty
Abstract
  • Additive Manufacturing is proving to be a revolutionary manufacturing process that is making itsway into all engineering industries that require high-performance and light-weight structuralcomponents. This is mainly thanks to its ability to manufacture complex shapes that areunobtainable by conventional processes, which allows designers to be freed from manufacturingconstraints and produce previously unmanufacturable components with unprecedented capabilities.Nonetheless, the fast adoption of additive manufacturing is hindered by poor orinconsistent material performance that is highly dependent on a component’s shape andmanufacturing parameters. Computational models that establish relationships between geometry,process parameters, and performance offer a valuable solution to overcome this challenge. Suchmodels can predict potential performance issues and guide the selection of optimal manufacturingparameters to prevent them. Nevertheless, developing these models is a complex task due to theintricate physics involved at different scales that impact the mechanical properties of an additivelymanufactured metal.This Ph.D. thesis proposes a multi-physics and multi-scale modelling approach to fullydigitally correlate the process parameters of selective laser melted Ti-6Al-4V with its elasto-plasticmechanical properties and structural performance. The method involves coupling micro-scalecrystal plasticity simulations to calculate mechanical properties with a component-scale thermalprocess model through a mean-field microstructure evolution model. The developed automatedmodelling tool could be used in optimisation of process parameters and geometrical design toachieve peak performance in additively manufactured structural components.Furthermore, a rigorous analysis of the developed model is presented with comprehensiveexperimental validation. Overall, the proposed Process-Structure-Property-Performanceframework demonstrated a strong foundation for improving the predictive accuracy of digitalstructural analysis of additively manufactured components. However, several limitations wereappreciated. The high computational cost of the thermal process model restricts its practicality foriterative optimisation frameworks, while the absence of damage and distortion modellingconstrains its predictive scope. Addressing these challenges will be essential to extend theapplicability of the framework and enable its integration into robust, industry-ready digital designand optimisation workflows.
Advisor / supervisor
  • Rahimi, Salaheddin
  • Huang, Jianglin
Resource Type
DOI
Date Created
  • 2025
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