Dr Chinnapat Panwisawas
BSc, PhD, CEng, FIMMM, FInstP, FIMechE

 

Research Impact

The academic and industrial impact of Dr Chinnapat Panwisawas' research in materials and manufacturing finds numerous applications in aerospace, automotive and biomedical sectors.

Top 2% of the World Scientists in 2022

Dr Panwisawas has been listed in Top 2% of the World Scientists in Materials for “single recent year impact” in 2022 published in PLoS Biol DOI: 10.17632/btchxktzyw.4  by Stanford University, USA.

Turbine blade manufacturing for future jet engine with Rolls-Royce University Technology Centre

The success of his previous industrial collaborative project between University of Birmingham, Rolls-Royce plc and ISIS Neutron and Muon Source (Science and Technology Facilities Council: STFC) to improve the predictive capability during turbine blade manufacturing has been recognised and published in the Science Highlights section of ISIS Annual Review 2017, which is selected from over 500 ISIS Neutron and Muon Source research papers published every year.

Innovative digital additive manufacturing using science-led in silico approach

The integrated computational materials engineering – an emerging digital approach to improve design and manufacture – is the first application to metal 3D printing and it is highlighted in the website of 3D Printing Industry (3DPI), a global media company in this field. The work led to a successful EPSRC Early Career Fellowship EPSRC UKRI Innovation Fellowship EP/S000828/1 and EP/S000828/2: From Industry 3.0 to Industry 4.0: Additive Manufacturability, aligned well with the UK Industry Strategy 2017/18 in digital technology. One of our articles has a significanct impact and has a FCWI of 9.5.

Predictive physics-based modelling for additive manufacturing of aerospace components

Computational framework of intermetallic precipitation leads to the First Place Award of AM-Bench 2018 Benchmark Challenge (CHAL-AMB2018-01-PFRS) organised by National Institute of Standards and Technology (NIST), USA. More information can be found at https://www.nist.gov/ambench/awards  It was recognised as the best modelling results predicting the phase evolution during residual stress annealing of an as-built IN625 bridge structure, which is beneficial to further develop for additive manufacture of nickel-based superalloys for aerospace applications.