The module aims to prepare students for professional practice, via an industry-led group project in advanced manufacturing systems.
Working in groups of four to six, students undertake computational and theoretical work and experience real industrial practice and processes through interactions with industry.
Over 12 weeks they develop a project plan, working on technical challenges designed to be representative of real industrial research and development projects.
As part of the ITP MAPP’s industrial partners - the Manufacturing Technology Centre (MTC), Wayland Additive and GKN Aerospace - provided direct technical support and expert process knowledge to a recent cohort.
The 74 students used digital learning and virtual meetings to overcome the challenges created by Covid-19.
This included a virtual poster workshop for industry and academics that allowed students to showcase their work in May 2020.
The posters summarised each group’s technical approach as well as main findings and recommendations.
Below is a poster created by a student taking part in The University of Sheffield’s Industry Training Programme (ITP) in 2020.
They included a poster (pictured above) answering the GKN Aerospace industry challenge, how to autonomously predict and classify defects in wire Laser Metal Deposition.
The student’s results showed more than 90 per cent accuracy on predicting and classifying unseen data by a Convolutional Neural Network modelling framework.
The 2019/20 module was led by MAPP’s joint X3 Theme Lead ACSE Professor George Panoutsos, Faculty Director of Research and Innovation - Faculty of Engineering.
The ITP’s activities, tasks and assessments are designed to give students the realistic experience of an industrial challenge, via working directly with industry as part of this module.
The 12-week module concludes with a poster presentation and this year the students overcame the challenge of Covid-19 restrictions by embracing digital learning and providing fantastic online poster presentations.
This year all projects and industry partners were MAPP-affiliated, demonstrating how MAPP is supporting taught programmes.
Professor George Panoutsos
Academic in the Department of Automatic Control and Systems Engineering (ACSE)
The project’s themes were:
- Active feedback control in Laser-Powder Bed Fusion
- Process optimisation in Additive Manufacturing using Machine Learning
- Electron Beam Melting process monitoring using Machine Learning
- Using deep learning to classify defects in Laser Metal Deposition - wire
- Process monitoring in Laser Metal Deposition – powder
A spokesperson for GKN Aerospace said:
“Your students have done really wonderful work.”
Students were positive about the module with one commenting in the ACS6402 ITP in Avionics student feedback questionnaire 2019/2020:
“I'm very glad I chose this as my optional module.”
The ITP relates to three ACSE MSc degrees; MSc Advanced Control and Systems Engineering, MSc Autonomous and Intelligent Systems and MSc Robotics.
MAPP’s X3 Theme: Modelling, Optimisation and Control aim is to turn the data and information from advanced processing and monitoring technologies into process understanding and control, via computational intelligence modelling and machine learning.
MAPP and INTEGRADDE (Intelligent data-driven pipeline for the manufacturing of certified metal parts through Direct Energy Deposition) Post-Doctoral Research Associate (PDRA) Scott Notley and VULCAN PDRA Bo Luo supported the 2019/20 ITP.