Don't miss our weekly PhD newsletter | Sign up now Don't miss our weekly PhD newsletter | Sign up now

  AI-Enhanced Self-Updating Digital Twin for Optimised Spray Drying in Dairy Manufacturing


   Research

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Dr Saritha Unnikrishnan, Dr Marion McAfee, Dr Emmett Kerr  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The Postgraduate Research Programme MedAgriTech AI eXcellence (MATX) offers 12 PhD research scholarships to commence in 2024. Each project will include an enterprise placement of minimum 12 weeks duration.

Project MATX 1: AI-Enhanced Self-Updating Digital Twin for Optimised Spray Drying in Dairy Manufacturing

Production of milk powders from fresh milk provides a vital mechanism for preserving nutritional value while enhancing longevity and enabling the distribution of dairy products to regions reliant on food imports. When reconstituted, this milk powder should ideally reflect the properties of fresh milk. However, the production process is complex and can result in unwanted changes in protein interactions and fat coalescence due to variations in process parameters which are difficult to monitor and control. This project investigates the potential of Artificial Intelligence (AI) and smart sensor technologies in developing a digital twin for enhanced quality control and efficiency in milk powder production. In stage one, the feasibility of using computer vision technologies combined with Deep Learning to identify relationships between e.g. powder particle size and shape and process variables will be investigated. Inline spectroscopy will be investigated, in stage two, for analysing milk protein structure and its impact on powder quality. A novel digital twin model will be developed using the experimental data obtained from sensor fusion, incorporating the significant variables identified from the analyses to self-update and enhance the spray drying process. 

A minimum of 2.1 honours degree (Level 8) in a relevant discipline.

Project Duration:

48 months (PhD)

Preferred Location:

ATU Sligo, Campus

Applications:

Application Form / Terms of Conditions can be obtained on the website: https://www.atu.ie/TU-RISE

The closing date for receipt of applications is 5pm, (GMT) Monday 29th April, 2024.

Only selected applicants will be called for an online interview (shortlisting may apply).

Computer Science (8) Engineering (12)

Funding Notes

TU RISE is co-financed by the Government of Ireland and the European Union through the ERDF Southern, Eastern & Midland Regional Programme 2021- 27 and the Northern & Western Regional Programme 2021-27.
Funding for this Project includes:
• A student stipend (usually tax-exempt) valued at €22,000 per annum
• Annual waivers of postgraduate tuition fee
• Extensive research training programme
• Support for travel, consumables and dissemination expenses

References

Essential Qualifications and Skills: First-class or High Second-class degree in Computer Science, Artificial Intelligence, Data Science or Engineering in a related discipline.
Desired Qualifications and Skills: Masters in the relevant disciplines. Computational Modelling and Simulation skills, Computer Vision and Deep Learning skills, and proficiency in Python programming
Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.