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Case Study

Glenrath Farms + University of Strathclyde

Develop an intelligent collaborative robot system for smart farm manufacturing (iCoBOTS).                                                              

Awards and Achievements

Winner of the KTP Images Event 2025 🏆

KTP Associate Nour Mohamed Morsi won the Best Image award at the KTP Images Event 2025

Glenrath Farms

Glenrath Farms is a family owned business that was established in 1959. We are based in the Scottish Borders and we are one of the UK's leading egg production and marketing companies, producing over a million eggs a day. We produce FreeRange, Organic, Barn and Enriched Colony eggs of which are compliant with UK and EU assurance schemes including Lion Quality, British Retail Consortium(BRC) and RSPCA Assured. We are the world's largest free-range egg producer.

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What was the need?

The Challenge

The primary challenge of this project is to develop and integrate an intelligent collaborative robotic system (iCoBOTS) within Glenrath Farms’ egg packing operations. The system must operate in a fast-paced, dynamic manufacturing environment, ensuring precision, reliability, and safety while handling fragile eggs.

A major hurdle is seamless human-robot collaboration, requiring advanced AI-driven perception, path planning, and adaptive control to enable cobots to work efficiently alongside human workers. Additionally, the cobots must minimise handling errors, reducing breakage while increasing throughput and operational efficiency.

Another challenge is the retrofitting of automation into an existing production line. Off-the-shelf solutions do not meet Glenrath’s specific needs, requiring custom hardware-software integration that aligns with industry regulations and safety standards.

Furthermore, the project must address staff resourcing issues by embedding expertise in robotic system design, optimisation and training, ensuring the workforce can effectively interact with and maintain the new system. Balancing technical innovation with commercial viability is key to achieving a scalable, cost-effective solution that enhances productivity and ensures long-term business sustainability.

What did we do?

The Solution

To address these challenges, the project will develop an intelligent collaborative robotic system (iCoBOTS) to automate the egg packing process. The system will utilise computer vision and real-time sensing to detect, classify, and handle eggs with precision, reducing breakage and increasing efficiency. 

A key innovation is the seamless human-robot interaction, where cobots will work safely alongside human operators. This requires adaptive motion planning, real-time perception, and intelligent control algorithms to adjust to dynamic factory conditions. 

The solution also involves custom hardware-software integration, ensuring compatibility with Glenrath Farms’ existing infrastructure without requiring a complete overhaul.

To support long-term sustainability, the project will embed robotics expertise within the company, developing a training framework for staff to operate, maintain, and improve the system. The result will be a cost-effective, scalable automation solution that enhances productivity, reduces reliance on manual labour, and ensures Glenrath Farms remains competitive in an evolving agricultural industry

What changed?

The Impacts and Benefits

Benefits for the Company 

  1. Organisational Impact:  Skills gap.  Will require a change in knowledge, attitudes, behaviours and skills.  Displace jobs traditionally requiring human labour, upskills existing employees to collaboratively work with the cobot. New ways of working and interacting
  2. Technological Impact: Integration of new technology will change the way we operate, hopefully enabling greater efficiency, collaboration and adaptability
  3. Financial Impact: Of acquiring and implementing new technology, which not only include the cost of the new technology, but also costs associated with training, infrastructure upgrades and potential disruptions during the transition

 

Benefits for the Academic Team

This project provides a significant opportunity for the academic team at the University of Strathclyde to advance research in robotics, AI-driven automation, and human-robot collaboration within a real-world manufacturing environment. The integration of machine learning, computer vision, and adaptive motion planning into a dynamic, safety-critical setting will contribute to key research areas such as digital manufacturing, Industry 4.0, and intelligent automation. 

Academically, the project will generate high-impact research outputs, including journal publications and conference presentations in leading venues such as IEEE Transactions on Robotics and International Journal of Advanced Manufacturing Technology.

Additionally, working on a real-world industrial challenge will enhance the team’s experience in technology transfer, industry collaboration, and commercialization of research. The project’s success may open doors for future grants, partnerships, and research funding, strengthening the university’s position as a leader in collaborative robotics and intelligent automation.

 

Benefits for the Knowledge Transfer Associate 

The Knowledge Transfer Associate (KTP Associate) will gain hands-on experience in developing and deploying an AI-driven collaborative robotic system (iCoBOTS) in a real-world industrial automation setting. This project offers a unique opportunity to apply robotics, machine learning, and system integrationexpertise in a dynamic manufacturing environment, bridging the gap between academic research and industrial application. 

The Associate will develop skills in robotic system design, adaptive motion planning, and real-time perception, working with cobots, sensors, and AI algorithms to optimize manufacturing processes. Additionally, they will gain experience in hardware-software integration, ensuring the cobots seamlessly interact with Glenrath Farms’ existing infrastructure. 

Beyond technical development, the Associate will enhance project management, leadership, and communication skills, collaborating with academics, engineers, and industry stakeholders. The role also offers opportunities for technical writing, publishing research papers, and attending conferences, strengthening their academic and professional profile. 

By the end of the project, the Associate will have industry-relevant expertise in robotics and AI, significantly improving their career prospects in automation, manufacturing, and intelligent systems.

The People

Meet the Team

Nour Mohamed Morsi

KTP Associate

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Dr Erfu Yang

Knowledge Base Supervisor

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Ashley Wallace

Company Supervisor

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