MSc Digital Manufacturing

This module aims to provide students with knowledge and understanding of the key concepts for Digital Manufacturing, current practices, tools and processes, and possible future development routes.

The module covers the current state of digital manufacturing, including tools and processes and identification of challenges and areas requiring further development in terms of research and technology innovation, product and service development, supplier management, production, routes to market, delivery, in service, maintenance, repair, remanufacture and reuse, and business plan development and management aspects. Digital manufacturing developments are also considered including the exploration of life-phases, challenges and technologies, Industry 4.0, Smart Products, Internet of Things, Cyber Physical Systems, value chains and value creation through life.

At the end of this module students will be able to:

• Demonstrate an understanding of the key concepts for digital manufacturing and stages of development of the manufacture of a chosen product
• Discuss different digital manufacturing approaches
• Provide an overview of the tools, processes and practices currently employed in digital manufacturing
• Identify challenges and opportunities for improvement
• Understanding of current worldwide initiatives for the future development of digital manufacturing, and exploration of how proposals for future development given would affect the current processes

Assessment and feedback is in the form of coursework (100%) including a group presentation and a report.

The module will teach the following topics:

• state-of-the-art of Digital Manufacturing
• introduction to the tools and processes currently employed in Digital Manufacturing
• identification of challenges and areas requiring further development in terms of research and technology innovation, product and service development, supplier management, production, routes to market, delivery, in-service, maintenance, repair, remanufacture and reuse, and business plan development and management aspects. Digital manufacturing developments
• exploration of life-phases, challenges and technologies required to meet those challenges
• introduction of initiatives for digital manufacturing development worldwide (Industry 4.0, Smart Products, Internet of Things, Cyber Physical Systems)
• benefits further development of digital manufacturing will bring
• value chains and value creation through life
• integration through life
• resources required

This module aims to introduce students to the concepts and basic technology of manufacturing automation and to be able to select suitable applications and specify the type of automation to be used in specific cases.

The module covers: Automation in manufacturing industry, why and where; Industrial robots, automation and typical applications; Open and closed loop control; Problems in robot design and control; Types of motion control; Control system functions; Advantages and disadvantages of electric and fluid power systems; Types of electric motors and their control techniques, simple actuators for hydraulic and pneumatic systems; Methods of programming robots; Relative economics of human labour, reprogrammable and hard automation and Safety considerations for industrial robots and other automated systems.

At the end of this module students will be able to:

• Demonstrate knowledge and understanding of why manufacturing automation is used
• Describe the conditions under which manual and/or automated production methods would be applied
• Analyse the configuration and technical specifications of an automation system suitable for a specified task
• Synthesise a manufacturing task suited to a specified automated system
• Analyse and understand the technological elements of drive and control, and machine vision, systems
• Critically appreciate the kinematic and dynamic problems associated with the control of automated systems
• Understand the implications of applying automation in human terms
• Demonstrate knowledge of safety factors that must be considered when installing automation

Assessment and feedback is in the form of one coursework submission showing technical analysis of an aspect of automation and critical thinking on the design of systems (40%), an exam (50%) and in-class participation (10%).

The module will cover the following topics: 

• mechatronic system design process: Product/system design specifications (PDS), concept generation and selection, mechatronic system design and flow chart diagrams.
• sensing and actuation: Sensing theory, sensor selection, drive design, motor control. 
• control systems: Understand and apply control theory in a mechatronic system design.
• hardware design: Processor architecture, embedded computing platforms, interface, I/Os.
• software design: Software design basics, algorithm and code design, programming tools, and software engineering principles.
• prototyping and evaluation: develop skills in selecting methods for prototyping using appropriate tools and means, including rapid prototyping and computer modelling.

This module aims to provide students with knowledge and understanding of the key concepts for the Design for Industry 4 and Smart Products, current practices, tools and processes, and possible future development routes.

The module covers the current and latest state-of-the-art in Design for Industry 4 and Smart Products, including the identification of challenges and areas requiring further development in terms of research and technology innovation, product and service development, supplier management, production, routes to market, delivery, in service, maintenance, repair, remanufacture and reuse, and business plan development and management aspects. It also explores the latest initiatives worldwide that tie with Design for Industry 4 and Smart products (Industrial Internet of Things (IIoT), Cyber Physical Systems, Cloud Manufacturing, Big Data analytics and Edge Analytics, Additive Manufacturing for Smart Products, IIoT Security aspects) and Through-Life Engineering and Through-Life Engineering Services (TES) concepts.

At the end of this module students will be able to:

• Formulate an overview of the tools, processes and best practice currently employed in Design for Industry 4 and Smart Products
• Understand initiatives currently undertaken worldwide for the future development of Design for Industry 4 and Smart Products, and assess how proposals for future development given would affect the current processes.

Assessment and feedback is in the form of classwork (100%) including a group presentation and a report.

This module provides the background and skills required to develop autonomous systems based on Machine Learning and Artificial Intelligence. Students will learn the theoretical as well as practical foundations of Data Science (Machine Learning, Deep Learning) for a design and engineering context. Laboratory exercises augment the taught classes to deepen the learning experience. The appreciation of responsible data collection and model training and the responsible design of sustainable solutions is a "golden thread" that runs throughout all lecture

This module aims to give students an understanding of the types of knowledge, techniques and systems used in building knowledge-based systems and discussion on the application of these techniques; and, an understanding of the types of different approaches, techniques and systems used in building information-based systems.

The module covers an introduction to knowledge based systems; knowledge representations; reasoning, chaining and searching and an introduction to information systems; information input and retrieval; information modelling process and techniques; information normalisation; visual modelling; information structure and organisation; and integration of information systems.

At the end of this module students will be able to:

• Demonstrate an understanding of Knowledge and Information Management
• Demonstrate an understanding of Knowledge Models and Methods
• Demonstrate an understanding of Knowledge Engineering and Development Processes
• Design, develop, implement and report on an appropriate information system to meet the identified information requirements

Assessment and feedback is in the form of group coursework (50%) and individual coursework (50%), there is no exam

This module aims for students to integrate and apply design, manufacturing and engineering management knowledge and skills to an industry based product and process development project and to develop project management skills.

The module consists of a team-based industrial project where an outline project brief is set by an industrial client. The team is expected to manage all aspects of the project through to a finished solution. This can be a product, system or process depending on the nature of the project. Teams meet with academic staff and industrial clients regularly through the project.

At the end of this module students will be able to:

• Have in-depth understanding and knowledge of products and management practices in industry
• Critically review and evaluate products and management practices of the particular company and the business impact of proposed solution
• Demonstrate knowledge and ability in applying and using various analysis and modelling tools and techniques
• Demonstrate project planning and management, presentation, consulting and team working skills
• Plan, control and lead an industrial project from inception to completion.
• Evidence achieving deliverables which meet the client company requirements.

Assessment and feedback includes a project report, a presentation to the client and any other deliverables specified in the project brief.

The aim of the individual project is to allow students to combine the skills learned in other modules of the course and apply them within a significant project in a specific area of design, manufacture, or engineering management. This will be achieved through students carrying out work into a particular topic relating to their course and preparing a dissertation that documents the project.

On completion of the module the student is expected to be able to:

• Define a valid project in a cutting-edge field of study relevant to the student’s degree – with an appropriate methodology and work plan for the project
• Plan, manage and complete project, involving where appropriate technical analysis and independent critical thinking. This involves giving a thorough, logical and critical review of the subject matter; using appropriate tools, processes and levels of analysis in the project and applying project management techniques to manage a successful project
• Document their project using suitable presentation techniques (such as language, figures, writing, layout, structure etc.); showing clear evidence of the value of the project and its outcomes and describing the project with clarity

Based on the work of a project, a student will submit an individual dissertation that will account for 90% of the final mark for the class. An interim project justification report will account for the remaining 10% of the mark.

The overarching theme for this course is creating, capturing, and delivering value with technology strategy.

The 11 lecturers will cover:

• How should one define a strategy for a technology-driven company? 
• How should such a strategy differ from a technology strategy?
• What should be the relationship between them? 
• When is a technology strategy useful?
• What should be its role?

1. Introduction scope and content of strategic technology management: An overview of strategy and technology management.
2. Introduction to frameworks for strategic analysis
3. Marketing-inspired strategic thinking
4. The industrial organization approach to strategy
5. Stakeholders and organizational politics strategic framework
6. Institutional theory and organizational culture strategic framework
7. Tools of technology management: The Technology S curves & the determinants of industry revolution
8. Tools for exploring new markets: The nature of the innovator's dilemma. 
9. Core concepts in network externalities: Technology Standards and the disruptor's dilemma.
10. Why responding to discontinuous technological change is so difficult and what can be done about it?

This module aims to provide students with an introduction to the fundamentals of advanced materials, characterisation and advanced surface engineering. The module also covers advanced machining processes and technologies and the principles and practices of rapid prototyping and manufacturing.

The module covers: Severe plastic deformation, materials properties and characterisation; Advances in Machining including the machining of hard materials, high-speed machining, precision grinding technology; ultra precision diamond turning and grinding technology; Principles and practice of Layered Manufacturing; Advanced Surface Engineering including physical-chemical functionalisation, electro-deposition, CVD, PVD, tools/mould treatment, nano- and multi-layered coating.

At the end of this module students will be able to:

• Describe processes of materials selection, characterisation, ultra-precision machining, rapid prototyping and advanced surface engineering
• Demonstrate know-how on key processing parameters and show numerical and analytical skills relating to the materials and process selections and parameter setting
• Identify key process parameters/variables in relation to process control and product quality
• Specify machines or manufacturing systems for the manufacture/creation of specified products/models or to propose design solutions for a manufacturing machine/system to address the manufacturing requirements identified

Assessment and feedback is in the form of four pieces of coursework (25% each).

This module aims for the student to acquire: (1) knowledge of the fundamentals of micro- and nano-products and of the manufacturing of such products (MEMS, micro-fluidic devices, micro-medical devices, micro-motors, microrobots, MOEMS, etc.), size-effects, material/interface behaviour at the micro-/nano-scale, challenges to manufacturing at low length-scales, etc.; (2) knowledge of micro-/nano-materials processing methods, techniques, industrially-viable processes, etc. and (3) experience and skills in the design/selection of micro- /nano-manufacturing processes, tools and equipment for real-world products.

It covers material behaviour, challenges, processes (subtractive, additive, deformation, replication, joining, hybrid processes including mechanical, thermal, chemical, electrochemical, electrical methods) and tools, machines and manufacturing systems.

At the end of this module students will be able to:

• Explain key techniques used in the processes for the manufacture of micro-products
• Correctly select technologies for specified products and materials
• Demonstrate calculations of forming/cutting forces involved and analysis of stresses/temperatures involved in tools/machine-frames/workpiece as appropriate
• Deliver a machine design (either for micro-machining or micro-forming) with detailed analysis and module designs, including a cost analysis on the machine designed.

Assessment and feedback is in the form of coursework (40%) and a project (60%), including a group project presentation and project report and individual assignment.

This module aims to introduce students to the theories and principles of Systems Thinking. The module also introduces the methods, tools and techniques for modelling, analysing, improving and designing systems in a variety of organisations including industrial, commercial and public sector.

The module covers: Systems theory, concepts and approaches; Hard and soft systems analysis and systems dynamics; Systems and organisational performance – including leadership in a systems environment and ‘design’ in a systems environment and Practical application of Systems Thinking.

At the end of this module students will be able to:

• show clearer understanding and knowledge of hard and soft approaches and how they can be used to deal with complexity and system behaviour in a business context
• develop understanding of fundamental cybernetic principles that form the foundations of Checkland’s Soft System Methodology and Beer’s Viable System Model
• develop knowledge and skills in systems analysis and business process modelling.
• critically evaluate the most appropriate methodology to model, analyse and design engineering/business systems across a range of organisations
• demonstrate an understanding of how to model a business system and to develop a solution to solve a business system problem
• cevelop an awareness of the importance of system approaches in management interventions

Assessment and feedback is in the form of a group presentation and one coursework in the form of a reflective diary.

This module covers one of the major challenges of modern industry which is to address the need for sustainable product development and manufacturing. International legislation and increasing costs of fiscal instruments such as the landfill tax now aim to force producers to reduce the environmental impacts of their products and processes. Accelerating globalization and industrialization continues to exacerbate complexity of sustainability. Whilst manufacturers are constantly required to lower their costs and maintain their competitiveness, legislations require them to look at lifecycle costs.

At the end of this module students will be able to:

• Understand the importance of sustainable product development and sustainable manufacturing and how to establish competitive advantage and appreciate the key legislation affecting modern industry
• Demonstrate an understanding of the engineers’ role in problem & solution to this and how to establish competitive advantage (e.g. via operational efficiency and effectiveness, new opportunities and enhanced enhancing marketing and customer goodwill)
• Describe End- of- Life issues and critically discuss the place of reuse processes in Sustainable Design and Manufacturing, as well as identifying the various reuse processes
• Identify the product features and characteristics that facilitate and hinder product recovery and redesign them for enhanced sustainability
• Identify the fundamental “building blocks” of LCA and describe/illustrate the use of LCA in lifecycle decision making, as well as describing Biomimicry use in product design

Assessment and feedback will be in the form of coursework (70%) and a lab project (30%).

This module focuses on innovation implementation. It integrates insights from research and strategy, management control, innovation and technology and organisational behaviour to consider how innovations can be managed. Three main challenges to innovation are explored: resources, organisation and management mechanisms.

The module covers: Management of Innovation including an overview of what makes innovation management complex and three models for how these complexities can be managed; Introduction to Model S for small initiatives; Introduction to Model R for Repeatable Innovations; Introduction to Model C for all other innovations; Build the Team: An Overview and Division of Labour; Assembling the dedicated team and managing the partnership; Creating the Innovation Strategy; Enabling, running and evaluating Disciplined Experimentations.

At the end of this module students will be able to:

• Demonstrate a comprehensive understanding of managing the innovation process within organisations
• Demonstrate how to integrate business strategy with innovating strategies
• Develop the ability to critically assess concepts, tools and techniques of managing innovation for both stable and turbulent environments
• Develop and contextualise an approach for analysis for a specific case
• Develop an innovation roadmap for strategic purposes

Assessment and feedback is in the form of a group presentation (40%) and an individual final report (60%).

Topic 1: Introduction to Machine Learning

Topic 2: MLP and Artificial Neural Networks

Topic 3: Backpropagation in Neural Networks Topic 4: Introduction to Deep Learning

Topic 5: Design and training of Deep Neural Networks

Topic 6: Convolutional neural networks

Topic 7: Recurrent Neural Networks

Topic 8: Spiking Neural Networks

Topic 9: Spike Time Dependant Plasticity

Topic 10: Implementation and deployment of Deep Learning

Topic 11: Review lectures in preparation for exam