Process Automation

The technical projects tackled during this module are varied and in most cases obtained from local companies who have a genuine engineering problem, design or development requirement. They can vary from research-orientated investigations of new methods or techniques to solution of shop-floor problems to improve productivity.

Projects are approximately eighteen-weeks in length and may be either selected from a ‘pool’ or self-proposed. Part-time students may undertake a project linked to their company subject to approval. Students are assigned an academic supervisor from the university and primary contact from the company.

During the project, students should assess the needs of an organisation and consider the required approach to delivering change; define a technical problem and critically appraise the nature of this problem; and finally identify various methodologies that could be appropriate for this problem situation and a sound project plan to implement them. From the initial ‘scoping’ to the final ‘closeout’ meeting the emphasis is on applying the skills learnt during the course to self-manage the project, identify and meet the requirements of all stakeholder and deliver a technically sound solution.

By the end of the module, postgraduates will have demonstrated the skills of independent learning and the ability for constructive critical reflection that is essential for continuing professional development.

This module provides an understanding of some of the higher level techniques and technologies used for process and system management, and decision support purposes. They require information, so a principal focus is upon the extraction of information from the platform of real-time data available within an integrated control and safety system (ICSS). It also provides an introduction to the technologies of fuzzy, neural and expert systems.

This module develops students’ appreciation of the interface between process automation and the wider interests of the business. In essence, real-time information abstracted from data within the ICSS by statistical means can be used in other applications for improving operations of the immediate process and beyond.

It also provides opportunity to develop the skills of independent working and effective communication.

This module provides an in-depth understanding of real-time model predictive control (MPC). It covers the techniques of identification and estimation used for developing the underlying models. Aspects of self-tuning are covered by way of introduction to MPC. The approach to MPC is introduced in the context of a single-input, single-output system and then extrapolated to multivariable systems. The key interface between MPC and real-time optimisation (RTO) is explained, and insight is provided on the limitations of the technology and implementation issues.

Students will develop awareness of the potential of MPC and its limitations. It is used for ‘difficult to control’ systems: those including non-linear, non-stationary, subject to delay, and multivariable. MPC is both complex and expensive. Fortunately, feedback control of a PID nature and related strategies can cope with some 95% of all applications. That leaves only 5% or less candidates for MPC.

The module also provides opportunity to develop the skills of independent working and effective communication.

A variety of unit operations are used as a vehicle for introducing various aspects of the design and operation of related plant and equipment items. The module also covers those aspects of chemical engineering, principally mass and energy balances, fluid flow and heat transfer, which are of particular relevance for understanding the nature of process operations and for building quantitative models of such

This module will enable students to better appreciate the wider societal impact of industrial, processes and plant and to make judgements about technical issues in an industrial context.

It also provides opportunity to develop the skills of independent working and effective communication.

This module provides a thorough grounding in the classical analysis and design of control systems using Laplace transform-based linear methods. In particular, for so-called single-input single-output (SISO) systems, it covers the use of transfer functions, block diagram algebra, interpretation of characteristic equation, frequency response and root locus.

Students will appreciate and understand the limitations of classical linear methods for the design of control systems for real processes and plant.

The module also provides opportunity to develop the skills of independent working and effective communication.

This module provides students with a sound understanding of all aspects of conventional 3-term control, covering the use of PID in both simple feedback and the related strategies of ratio, cascade and feedforward control. It also covers the classical approaches to and schemes for the control of a variety of items of process plant, as well as the basics of sequence control.

This module will enable students to better appreciate and understand the potential impact of process automation on company performance, and indeed its wider societal impact, and to make judgements about technical issues in an industrial context.

It also provides opportunity to develop the skills of independent working and effective communication.

This module provides students with an understanding of the functionality of the hardware, system software and application software (both configurable and procedural) of integrated control and safety systems (ICSS), whether they be of a distributed control system (DCS), supervisory control and data acquisition (SCADA) or programmable logic controller (PLC) nature. There is a particular focus on application software, its organisation, constructs, tools for development, and good practice.

The module will develop students’ ability, tempered by a healthy scepticism, to distinguish between aspects of control technology, including that are necessary/desirable, robust/not proven, feasible/impracticable, viable/unsustainable, real/virtual, and trusted/fashionable. It also provides opportunity to develop the skills of independent working and effective communication.

This module provides students with an in-depth understanding of the ‘layers of safety’ approach to plant and process safety and the distinction between layers, identification and analysis of requirements for independent protection systems, quantitative design and deployment of SIL rated protection systems, and the nature of cyber risk to both control and protection systems, and the means of mitigating against breaches of security.

The module will enable students to better understand the contribution of automation to process safety, related societal issues, and to appreciate its limitations in terms of reliability and security. It also provides opportunity to develop the skills of independent working and effective communication.

The module provides students with a thorough grounding in the principles, technology, infrastructure and practices of instrumentation used for the measurement of common variables such as flow, level, pressure and temperature. There is an emphasis on the specification, installation and operation of instrumentation as well as on final elements such as control valves.

This module will enable students to better appreciate the safety and sustainability implications of the use of instrumentation on process plant and to make related judgements about technical issues in an industrial context. It also provides opportunity to develop the skills of independent working and effective communication.

The module provides students with an understanding of the issues involved in the management of control and automation projects. It is based upon the life cycle of an automation project, from costs and benefits analysis, specification right through to operation, maintenance and support. Aspects of management are considered from both an end user’s (operating company) and supplier’s (system vendor) perspective. The emphasis throughout is upon good project management practice.

This module enables students to understand the scope for influencing through project management, and the impact of process automation upon company performance and beyond. It also provides opportunity to develop the skills of independent working and effective communication.

This module concerns the development of first principles dynamic models of items of processes, and items of plant and equipment, and the simulation of those models for analysis and control system design purposes. The emphasis is on input-output relationships. There is a focus on making assumptions and approximations such that, rather than seeking perfection, the models developed are ‘good enough’.

The module will enable students to better appreciate and understand the constraints on effective operation of process plant and equipment, and to make judgements about technical issues in an industrial context. It also provides opportunity to develop the skills of independent working and effective communication.

This module provides students with a grounding in the techniques used for handling sampled data signals. The state-space approach to modelling is developed for systems involving either continuous and/or sampled data signals. Based upon state-space, the techniques of state feedback and observer design are introduced. These various techniques provide the basis for analysis and design of so-called multi-input multi-output (MIMO) control systems, and consideration of approaches to the implementation of multivariable control strategies.

The module will enable students to appreciate and understand the complexity and limitations of the various theoretical techniques available for the design of multivariable systems. Students will able to make judgements about relevant technical issues in an industrial context and also develop independent working skills, and effective communication.

The module provides students with an in-depth understanding of the principles underlying various techniques of optimisation and scheduling, especially optimisation of a constrained nature with multiple decision variables in a real-time context. It also introduces students to the technology and practices in the use of real-time optimisers (RTO) in the process industry. The two principal categories of RTO are covered, steady-state and dynamic, with a particular emphasis on the dynamic type.

This module will enable students to look at a process or plant from the perspective of optimising its performance. It is possible to optimise performance with respect to several independent variables simultaneously and subject to constraints: that is a very powerful capability. The control objectives become self-evident and translate into targets for the control system.

The module provides students with a thorough grounding in the principles, technology and practices of analytical measurement, with an emphasis on the specification, installation and operation of the types of analyser, analytical measurement, and sampling systems commonly used for the real-time monitoring and control of industrial plant and processes.

This module enables students to appreciate and understand the role of process automation in the monitoring of emissions, their potential for reduction and environmental impact. It also provides opportunity to develop the skills of independent working and effective communication.