ACS6403 Industrial training programme (ITP) in Computational Intelligence

Module Description (subject to change)

This unit will provide an insight into advanced Computational Intelligence systems via industry-relevant project work. This will be collaboration with an industrial partner. The industrial partner will set a real technical challenge and student groups will undertake practical and theoretical work and present a report that will also require an in-depth literature review. To supplement the main technical challenge there will be focussed technical seminars on relevant topics. These topics will be provided by both academics and industry engineers. In addition, the industrial partner will provide seminars relevant to both professional and technical skills to help students complete the project.

Places in this optional module are limited; subject to availability and to students’ performance in the first semester of the MSc programme.

Credits: 15 (Spring semester)

Please note that this module is exempt from the University’s General Regulations relating to Intellectual Property

Module Leader

George Panoutsos












Dr George Panoutsos

Email: g.panoutsos@sheffield.ac.uk
Amy Johnson Building

If you have any questions about the module please talk to me during the lectures or the labs in the first instance. It is likely that other students will learn from any questions you ask as well, so don’t be afraid to ask questions.

Outside of lectures please contact me via email, or drop in to see me.

Learning Outcomes

Learning Outcomes

By the end of the module students will be able to:

  • Identify system design changes in advanced manufacturing systems, in order to improve performance when specific components are manufactured and used in service (EA1fl, EA2fl).
  • Identify, apply and analyse an appropriate Computational Intelligence technical approach needed to assess the performance of a specific manufacturing task and disseminate the findings (EA3fl, D2fl).
  • Demonstrate a general understanding of advanced manufacturing and Computational Intelligence - based process monitoring techniques for the manufacture of critical components (D1fl).
  • Accept responsibilities, formulate ideas proactively, deal with open-ended and unfamiliar problems, plan and develop strategies, implement and execute agreed plans, lead and manage teams where required, evaluate achievement against specification and plan, and decision-making (D3fl, ET1fl, ET2fl,ET3fl, ET4fl, ET5fl, ET6fl).

This module satisfies the AHEP3 (Accreditation of Higher Education Programmes, Third Edition) Learning Outcomes that are listed in brackets after each learning outcome above. For further details on AHEP3 Learning Outcomes, see the downloads section of our accreditation webpage.

Syllabus

Syllabus

The syllabus will depend on the group project. It will typically have some level of technical difficulty involving theoretical concepts, and have a significant level of practical/computational topics.

Teaching Methods

Learning and Teaching Methods

NOTE: This summary of teaching methods is representative of a normal Semester. Owing to the ongoing disruption from Covid-19, the exact method of delivery will be different in 2020/21.

To meet the learning outcomes the basic course content will be delivered by academic workshops, site visits (industry partner), seminars on the process under investigation, technical seminar case studies by industry, and specific lectures by academics supported by supplementary material on Blackboard (MOLE) for use in independent learning. Independent study is also expected to be used for additional reading around the topic area. This will be essential in enabling students to develop an appropriately deep understanding of the project under investigation.

  • Lectures: 12 hours
  • Seminars: 12 hours
  • Fieldwork: 20 hours
  • Independent Study: 106 hours
Teaching Materials

Learning and Teaching Materials

All teaching materials will be available on Blackboard (MOLE).

Assessment

Assessment

This module is 100% coursework.

Group project (40%)

Coursework (60%)

Feedback

Feedback

  • Feedback will be continuously provided throughout the semester, via the scheduled tutorial support sessions.
  • Assignments/Reports: Coursework is returned marked to the students, along with individual and group feedback as appropriate.
  • A Discussion board will be available in this module to give responses to student queries on Blackboard (MOLE).
Student Evaluation

Student Evaluation

Students are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of each semester.

You can view the latest Department response to the survey feedback here.

Recommended Reading

Recommended Reading

Recommended reading depends on project topic, and will be advised during the support sessions. Examples include:

  • Astrom, K.J. and Murray, R.M (2009), Feedback Systems – An Introduction for Scientists and Engineers
  • Blanchard, B and Fabrycky, W J (2006). Systems Engineering and Analysis (Fourth Edition). Prentice Hall, New Jersey, USA
  • Kossiakoff, A and Sweet, W N (2003). Systems Engineering Principles and Practice. Wiley, New Jersey, Massachusetts, USA [available in Information Commons, 620.0011(S)]