Controlling structure, form and function for engineering alloys processed by additive manufacture (AM)

Lead Research Organisation: University of Sheffield
Department Name: Materials Science and Engineering

Abstract

Controlling structure, form and function for engineering alloys processed by additive manufacture (AM) is essential if we are to reduce secondary operations such as HIP or heat treatment.

There are however, challenges in exerting this degree of control. Presently AM systems operate using "fixed" processing parameters and monitoring, where performed, tends to focus on the movement, as a result of thermally induced stress, of components during the build or on simple detection of defects.

Within the MAPP EPSRC Future Manufacturing Hub (Sheffield, Oxford, Manchester, Leeds and Imperial College London) we are seeking to develop such an approach.

To facilitate this, in this PhD research we will combine In-process and In-situ characterization and measurements, employing novel in-process measurements (High speed, High Resolution Thermal imaging, hyper-spectral imaging, mass spectrometry etc.) with beam-line x-ray imaging experiments at the Diamond Complex at Harwell to give new insight into this highly complex process.

The researcher would be part of a large, multidisciplinary team at the University of Sheffield, and integrated into the wider MAPP Hub and network, and supported by Rolls-Royce.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R512175/1 01/10/2017 30/09/2021
1963745 Studentship EP/R512175/1 25/09/2017 04/04/2022 Lev Chechik
 
Description The additive manufacturing process is very complicated, but many parameters can be altered to reduce the likelihood of issues.
This work has shown that there are simple geometric changes which can be made to improve component dimensions (and reduce swelling).

Further, an in depth analysis of thermal data is starting to show that the final parts properties can be predicted by the temperature in the process.
Exploitation Route This work can change the way in which components are designed to improve the final outcome.
Monitoring of the process can inform the operator of the final properties, giving a better insight than before and reducing the need for destructive testing.
Sectors Aerospace, Defence and Marine,Manufacturing, including Industrial Biotechology

 
Title 316L Steel DED Coaxial Thermal Data 
Description Additive Manufacturing in the BeAM Magic 2 using 316L steel. Thermal data captured using a Silicon camera coaxially when printing a variety of components including different parameter sets. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? No  
Impact When changing processing parameters, the coaxial signal changes. By extracting simple features from the images, K-means clustering can be used to differentiate between different parameter sets. 
 
Title 316L Steel DED Side on Thermal Data - Telecentric Lens 
Description Using an InGaAs camera to capture side-on imaging of the DED process. This was performed for a range of parameters and geometries 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? No  
Impact Various comparative features can be extracted, such as cooling rates, melt pool sizes etc. These can then be correlated to materials properties e.g. hardness. 
 
Title Scripts for analysing thermal data captured during DED Process 
Description Matlab scripts for extracting times of images and calculating cooling rates, melt pool sizes etc. Also link these to position in component using axis positions. 
Type Of Material Data analysis technique 
Year Produced 2020 
Provided To Others? No  
Impact Starting to correlate the thermal signature of the process to the final component properties.