MPhil project: 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.
Supervisor:
Student Requirements for this Project
Applicants should hold a minimum of a Bachelor's degree or an equivalent qualification in Electronic Engineering, Electrical Engineering, Automation Engineering, Mechatronics, Computer Engineering, Computer Science, Software Engineering, Data Science, or a related discipline.
This project is particularly suitable for candidates with an interest in one or more of the following areas:
Artificial Intelligence and Machine Learning
Generative AI and Large Language Models (LLMs)
Industrial Automation and Control Systems
SCADA and Industrial Monitoring Systems
Human-Machine Interfaces (HMI)
Industrial Internet of Things (IIoT)
Data Analytics and Decision Support Systems
Software Development and Programming
Experience in programming using Python, Java, C/C++, or similar languages is desirable. Familiarity with AI frameworks, databases, cloud platforms, automation software, PLCs, SCADA systems, or industrial communication protocols would be advantageous but is not essential.
The successful candidate should demonstrate:
Strong analytical and problem-solving abilities.
An interest in emerging AI technologies and their industrial applications.
The ability to work independently and manage a research project effectively.
Good written and verbal communication skills in English.
A willingness to engage with interdisciplinary research spanning AI, automation, and industrial digitalisation.
This project is especially attractive to candidates seeking careers in Industrial AI, Smart Manufacturing, Digital Transformation, Industrial Automation, Process Engineering, or Intelligent Decision Support Systems. The research will provide valuable skills in Generative AI, industrial software development, automation technologies, and Industry 5.0 applications.
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.
Supervisor:
Student Requirements for this Project
Applicants should hold a minimum of a Bachelor's degree or an equivalent qualification in Electronic Engineering, Electrical Engineering, Automation Engineering, Mechatronics, Computer Engineering, Computer Science, Software Engineering, Data Science, or a related discipline.
This project is particularly suitable for candidates with an interest in one or more of the following areas:
Artificial Intelligence and Machine Learning
Generative AI and Large Language Models (LLMs)
Industrial Automation and Control Systems
SCADA and Industrial Monitoring Systems
Human-Machine Interfaces (HMI)
Industrial Internet of Things (IIoT)
Data Analytics and Decision Support Systems
Software Development and Programming
Experience in programming using Python, Java, C/C++, or similar languages is desirable. Familiarity with AI frameworks, databases, cloud platforms, automation software, PLCs, SCADA systems, or industrial communication protocols would be advantageous but is not essential.
The successful candidate should demonstrate:
Strong analytical and problem-solving abilities.
An interest in emerging AI technologies and their industrial applications.
The ability to work independently and manage a research project effectively.
Good written and verbal communication skills in English.
A willingness to engage with interdisciplinary research spanning AI, automation, and industrial digitalisation.
This project is especially attractive to candidates seeking careers in Industrial AI, Smart Manufacturing, Digital Transformation, Industrial Automation, Process Engineering, or Intelligent Decision Support Systems. The research will provide valuable skills in Generative AI, industrial software development, automation technologies, and Industry 5.0 applications.
