Intelligent data-driven pipeline for the manufacturing of certified metal parts

Intelligent data-driven pipeline for the manufacturing of certified metal parts through Direct Energy Deposition process (INTEGRADDE)

INTEGRADDE aims to develop an end-to-end Digital Additive Manufacturing (AM) solution, based on DED technologies [i.e. Laser Metal Deposition (LMD) for manufacturing of complex geometries in medium-sized components with higher accuracy, and Wire-Arc Additive Manufacturing (WAAM) for simpler geometries with higher deposition rates] enabling a cybersecured bidirectional dataflow for a seamless integration across the entire AM chain.

The goal is to develop a new manufacturing methodology capable of ensuring the manufacturability, reliability and quality of a target metal component from the initial product design.

INTEGRADDE combines research on building strategy optimisation, multi-scale and multi-physics modelling, hardware-independent building process, automatic building strategy generation, online self-adaptative control and inline quality assurance for the manufacturing of certified metal parts, addressing mass customisation manufacturing approach.

Meet the Principal Investigator(s) for the project

Professor Zidong Wang - Zidong Wang is a member of Academia Europaea, a Member of the European Academy of Sciences and Arts, an IEEE Fellow and Professor of Computing at Brunel University London, UK. He has research interests in intelligent data analysis, statistical signal processing and dynamic systems & control. He has been named as the Hottest Scientific Researcher in 2012 in the area of Big Data and listed as highly cited researchers in categories of both computer science and engineering in 2015-2020 with an h-index of 139. He is currently serving as the Editor-in-Chief for International Journal of Systems Science, the Editor-in-Chief for Neurocomputing, the Editor-in-Chief for Systems Science and Control Engineering, and Associate Editor for other 12 prestigious journals including 5 IEEE Transactions.  His research has been funded by the EU, the Royal Society and the EPSRC. 

Related Research Group(s)

Digital Manufacturing - Being at the forefront of solutions for building smart machines, we create an operational framework for the digital transformation to Industry 4.0.

Intelligent Data Analysis - Concerned with effective analysis of data involving artificial intelligence, dynamic systems, image and signal processing, optimisation, pattern recognition, statistics and visualisation.

Partnering with confidence

Organisations interested in our research can partner with us with confidence backed by an external and independent benchmark: The Knowledge Exchange Framework. Read more.

Project last modified 20/07/2021