Throughout the 2024 European Project Semester at Glasgow Caledonian University, our team worked on a project for Howden, a global industrial company with a significant presence in Glasgow. Howden is renowned for manufacturing a wide range of industrial fans used across various sectors. The specific project we were tasked with was titled “Fan Blade Wear.” Our objective was to develop a computational tool that could predict wear on fan blades based on mechanical data. In this report, we will walk you through the comprehensive process we undertook during the fifteen weeks of this project to meet the objectives set by Howden and our academic supervisors. We begin with brief introductions of our team members and then provide a detailed context for the project. Next, we describe the project management methodologies we implemented to ensure effective progress toward our goals. Following this, we delve into the design-thinking phase, where we brainstormed and conceptualized our approach. We also recount our site visit to Howden's Glasgow factory. The subsequent section focuses on our research phase, a crucial step that informed the development of our predictive algorithm. We then explain how we created this algorithm to calculate fan blade wear, followed by a comparison of our results with data from Howden. We also discuss the Computational Fluid Dynamics (CFD) simulations we ran to validate our findings. In the final sections, we outline how the algorithm can be implemented in an industrial context and describe the design of the website that will support its application. The report concludes with our final thoughts and reflections on the project, summarizing the lessons learned and the outcomes achieved. Overall, this report is a comprehensive account of our journey through the European Project Semester, demonstrating our collaborative efforts and the innovative solutions we developed for Howden.
Treball desenvolupat en el marc del programa "European Project Semester".
