- Academic Registry
Course & Unit Catalogues


CE52002: Automation, manufacturing and design

[Page last updated: 16 August 2024]

Academic Year: 2024/25
Owning Department/School: Department of Chemical Engineering
Credits: 10 [equivalent to 20 CATS credits]
Notional Study Hours: 200
Level: Masters UG & PG (FHEQ level 7)
Period:
Semester 2
Assessment Summary: CWRG 100%
Assessment Detail:
  • Automation, manufacturing and design report (CWRG 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites:
Learning Outcomes: Apply and evaluate the steps in digital manufacturing and design processes, from data collection, process optimisation, process control to data analysis.
Collaborate in a digital manufacturing and design environment
Plan, develop and deploy ML solutions in digital manufacturing and design


Synopsis: Explore how automation, digital design and manufacturing are driving change to more efficient and sustainable processes. You'll learn about the roles of big data, digital twins, internet of things, and internet 5.0, and more. Working in groups, you'll develop ML models, train, and validate them using data you've collected. You'll run and evaluate your model to identify ways to improve its resilience.

Aims: Explore how automation, digital design and manufacturing are driving change to more efficient and sustainable processes and uncover the role of big data, digital twins, internet of things, and internet 5.0. Work in groups to develop ML models, train and validate them using data you collected. Implement and evaluate your model and identify ways to improve its resilience.

Skills: Data collection, validation, interpretation, evaluation. Group working.

Content: Drivers for digital transformation in manufacturing and design across the engineering disciplines
Building blocks of Industry 4.0 and Industry 5.0 paradigms
Internet of things
Cyber-physical systems
Digital twins
Process optimisation
Instrumentation and control
Additive manufacturing
New business opportunities.

Course availability:

CE52002 is a Must Pass Unit on the following courses:

Department of Electronic & Electrical Engineering
  • TEEE-AFM22 : MSc Artificial Intelligence for Engineering and Design
  • TEEE-AWM22 : MSc Artificial Intelligence for Engineering and Design

Notes:

  • This unit catalogue is applicable for the 2024/25 academic year only. Students continuing their studies into 2025/26 and beyond should not assume that this unit will be available in future years in the format displayed here for 2024/25.
  • Courses and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.