Modules

Below you can find a list of all third year modules. Some modules in this year are optional.

Modules

Design Art Creativity (optional)

This module will explore the fine arts and their potential for influencing design engineering. Students will develop an understanding of the design landscape today; including trends, design methodologies, and social and environmental responsibilities and to develop visual communication skills, creative expression, and ethnographic understanding to be able to ideate and innovate appropriately to a brief.

Students will develop their communication skills through sketching, drawing, scribbling, interpreting, conveying and learn to keep an open mind through brainstorming, thinking, ideating and innovating. Students will be introduced to design processes and methodologies and learn to identify opportunities for improvement and develop briefs.

Assessments will include presentations, peer reviews, and critiques.

Engineering Design Management and Rationale

This module explores a meta-theme and user personas to develop a value proposition for a new enterprise. The premise for this course is that successful design-led innovation depends on blending customer insight and technical inventiveness to create value for customers and users as well as commercial value for innovative firms and their investors.

Students will be introduced to key concepts in design, creative problem solving, prototyping and the disciplines of human centred design. The second part of the course focuses on new venture creation where students will learn about the most relevant theoretical models and best practice.

The course is made up of formal teaching sessions that run alongside, and inform, a team project that focuses on a real problem in a particular domain. Teams are regularly coached throughout the course to ensure the newly introduced tools are applied appropriately, to ensure the best possible project outcomes.

Design Led Innovation and Enterprise (optional)

This module explores a meta-theme and user personas to develop a value proposition for a new enterprise. The premise for this course is that successful design-led innovation depends on blending customer insight and technical inventiveness to create value for customers and users as well as commercial value for innovative firms and their investors.

Students will be introduced to key concepts in design, creative problem solving, prototyping and the disciplines of human centred design. The second part of the course focuses on new venture creation where students will learn about the most relevant theoretical models and best practice.

The course is made up of formal teaching sessions that run alongside, and inform, a team project that focuses on a real problem in a particular domain. Teams are regularly coached throughout the course to ensure the newly introduced tools are applied appropriately, to ensure the best possible project outcomes.

Robotics 1

This course is an intermediate course in robotics, sensors, actuators, and control, building on the DE2-Giz module.

We will emphasize both theoretical and practical aspects of the field. We will start by looking at the basics of wheeled locomotion, and proprioceptive and outward-looking sensors, and examine how these can be coupled in direct servo loops to produce reactive behaviours. We will then look at how different behaviours can be combined to produce more complicated activity via architectures such as subsumption.

This is a course with an intensive practical element, and every week there will be practical sessions in the laboratory where students will work in groups with Lego Mindstorms NXT kits and the RobotC programming environment. Marking of the assessed coursework component is cumulative: every week there will be a task set to each group and marks will be given for successfully demonstrating results in the next practical session.

At the end of the course students will be familiar with the key concepts related to the building and programming of autonomous robots. They will understand the different kinds of locomotion and sensor systems that can be used, and the principles behind the programming of simple reactive behaviours. They will understand different ways in which reactive behaviours can be programmed and combined for controlling a robot in an unknown but fixed type of environment. They will have been introduced to advanced techniques in probabilistic filtering, simultaneous localisation and mapping, and motion planning.

Optimisation 1 (partially optional)

1.1 - Fundamental Optimisation

This course is an introduction to System Design with an overview of review of design, architecting, systems thinking, system life cycle models and functional allocation. Topics include:

Systems Design and Optimisation I — Concepts: optimisation formulations, optimisation and QFD, Pareto optimality and computer software introduction.Basic Numerical Analysis: system modelling, state space models, classification, linear systems, numerical integration, numerical algorithms, linear programming, constrained and unconstrained problems using MatLab and Excel tools.Problem Formulation: optimality concepts, convexity and constrained problems. Differential Theory and Bounded Optima: local approximation, convergence, gradient methods, Newton optimisation and Lagrange multipliers.Numerical Solutions: implementation of algorithms, convergence, programming, cost function.System Design Optimisation II — Implementation: practical modelling and implementation examples, design optimisation and product development.

1.2 - System Design and Applications (optional)

This module extends the tools of analysis introduced in Optimization 1.1 to systems thinking and the processes and methods of design optimization and systems engineering. Multi-objective design optimization will be introduced as a follow-on to single objective and amalgamated approaches covered in Optimization 1.1.

The course covers fundamentals of decision making, trade-off analysis, systems engineering and system architecting, requirements analysis, and optimal system design. Extensive use of software tools for optimization based on mathematical programming (Matlab), spreadsheet analysis (Excel), and model based system design (e.g. CORE) will be introduced in project-based work. The course includes the application of fundamental systems engineering processes and methods in the context of modelling and optimal decision making.

At the close of the module, students should be able to create a multi-objective optimization model reflecting multi-parameter design and implement software tools to solve these problems.

Group Project

In this module, students will work on an interdisciplinary group project group to explore user requirements with insights from users. Students will develop strong team work and project management skills as well as detailed design, design protototying and rapid prototyping. At the end of the project, students will exhibite their group work.

Industry Placement

The six-month Industry Placement aims to provide practical industry experience on a substantial project.

The placements will run April - September in the third year. Third year exams will be taken early to ensure that all students will be present in College. Please note, as a result of the placement, that there is not the traditional extended holiday period between the third and fourth year.

The UG office and course leader will arrange for students to be matched with companies. Care will be taken to ensure that appropriate companies and industrial supervisors are selected, which are prepared to provide suitably challenging and well-defined project objectives to students. Companies will be generally expected to pay the students at a level appropriate for a new graduate.

The students will have two School supervisors and one industrial supervisor. The module will be assessed against objectives by the Schools supervisors on the basis of an interim and final report, a presentation, a site visit by the supervisors, and an employer’s report from the industrial supervisor.