You develop an understanding of the principles and technology of analytical measurement systems. Within this, limitations of accuracy are studied along with operational requirements of analytical sensor elements.

This module also investigates the recent generations of sensor systems based on microprocessor systems, application-specific integrated circuits and microcontrollers.

Using relevant industrial examples, smart sensors are analysed and synthesised using modern programming methods and up-to-date devices.

Explore the control system design techniques for Single Input Single Output (SISO) continuous systems using classical control theory and state space methods.
You develop practical techniques of creating and simulating linear and dynamic models, and provided with an introduction to non-linear systems and models.

Modern processes and products are often highly dependent on digital control and instrumentation systems to keep them operating in a safe, efficient and economical manner.

You develop your knowledge of discrete-time computer-based control systems, digital control and signal processing, industrial informatics and related components and software.

This module advances the development of your independent learning skills by allowing you to investigate an area of engineering for an extended period. You are given training in writing technical reports for knowledgeable readers and you produce a report or dissertation of the work covered. You also give an oral presentation, a poster presentation or both. The topic can be in the form of a research project or a design project. You develop key skills in research, knowledge application and creation through keynote lectures where appropriate and self-managed independent study. You are supported through regular tutorial sessions and project supervision meetings.

The emergence of Industry 4.0, often referred to as the fourth industrial revolution, has been attributed to advancing automation, decentralisation and system integration and cloud computing. In the cyber-physical environment, machines can communicate, collect information, and make informed decisions through artificial intelligence (AI), big data and industrial internet of things (IIoT). The evolution of Industry 4.0 has great potential to improve the energy, equipment, and human behaviour. At the same time, in the era of the so-called circular economy, industry across all sectors is under huge pressure to make their manufacturing operations ethical and sustainable. Therefore, we must learn to adopt or implement the latest Industry 4.0 technologies.