Generative AI for Industrial Automation and SCADA Systems

The increasing adoption of Artificial Intelligence (AI) in industry is creating new opportunities to enhance the operation, monitoring, and maintenance of industrial automation systems. Generative AI technologies, including Large Language Models (LLMs), have demonstrated significant potential for supporting decision-making, interpreting complex technical information, and improving human-machine interaction. However, their application within Supervisory Control and Data Acquisition (SCADA) systems and industrial automation environments remains largely unexplored.

This MPhil project aims to investigate the use of Generative AI to enhance the intelligence and usability of SCADA systems. The research will explore how AI-powered assistants can support operators in monitoring industrial processes, diagnosing faults, interpreting alarms, generating maintenance recommendations, and accessing technical documentation through natural language interaction.

The project will involve a review of current AI and SCADA technologies, the development of a prototype AI-assisted SCADA framework, and the evaluation of its effectiveness using simulated industrial scenarios. Particular attention will be given to improving operational efficiency, reducing response times to system faults, and enhancing the accessibility of industrial data for operators and engineers.

The research aligns with Industry 5.0 priorities by promoting human-centric industrial systems that combine automation with intelligent decision support. Potential application areas include manufacturing, utilities, building automation, and process industries.

The successful candidate will gain expertise in Artificial Intelligence, Industrial Automation, SCADA Systems, Human-Machine Interfaces, and Industrial Data Analytics. The project is expected to generate conference and journal publications and provide valuable skills relevant to modern industrial digitalisation initiatives.

The increasing adoption of Artificial Intelligence (AI) in industry is creating new opportunities to enhance the operation, monitoring, and maintenance of industrial automation systems. Generative AI technologies, including Large Language Models (LLMs), have demonstrated significant potential for supporting decision-making, interpreting complex technical information, and improving human-machine interaction. However, their application within Supervisory Control and Data Acquisition (SCADA) systems and industrial automation environments remains largely unexplored.

This MPhil project aims to investigate the use of Generative AI to enhance the intelligence and usability of SCADA systems. The research will explore how AI-powered assistants can support operators in monitoring industrial processes, diagnosing faults, interpreting alarms, generating maintenance recommendations, and accessing technical documentation through natural language interaction.

The project will involve a review of current AI and SCADA technologies, the development of a prototype AI-assisted SCADA framework, and the evaluation of its effectiveness using simulated industrial scenarios. Particular attention will be given to improving operational efficiency, reducing response times to system faults, and enhancing the accessibility of industrial data for operators and engineers.

The research aligns with Industry 5.0 priorities by promoting human-centric industrial systems that combine automation with intelligent decision support. Potential application areas include manufacturing, utilities, building automation, and process industries.

The successful candidate will gain expertise in Artificial Intelligence, Industrial Automation, SCADA Systems, Human-Machine Interfaces, and Industrial Data Analytics. The project is expected to generate conference and journal publications and provide valuable skills relevant to modern industrial digitalisation initiatives.

Self Funded  - Scholarship not available. Fees & Materials to be paid by the student. 

If you are interested in submitting an application for this project, please complete an Expression of Interest.

 https://forms.office.com/e/0hCcrv2Gkp