Dr. Niladri Chakraborty is a lecturer as the Department of Mathematical Statistics and Actuarial Sciences, University of the Free State, South Africa. He earned his PhD in Mathematical Statistics from the University of Pretoria in 2017. Prior to joining the University of the Free State, he worked as a postdoctoral researcher at the City University of Hong Kong. His main research interests are in statistical process control and nonparametric inference.
In this paper, a multivariate process monitoring scheme based on the rank-energy statistic is proposed which is suitable for high-dimensional applications such as sensorless drive diagnosis. The rank-energy statistic is based on multivariate ranks that is grounded on the measure transportation theory. Univariate ranks could be interpreted as a solution to an optimization problem involving a given set of observations of size n and the set {1,2,3,..,n}. Recently, attaining greater robustness than spatial sign or depth-based ranks, multivariate ranks are proposed as solutions to such optimization problem in multivariate settings (measure transportation problem). The proposed multivariate process monitoring scheme based on the rank-energy statistic, subsequently, attains greater robustness than existing nonparametric multivariate process monitoring methods based on spatial sign or depth-based ranks. The proposed method is also applicable to high-dimensional data unlike some of the existing nonparametric multivariate process monitoring methods. A rigorous simulation study demonstrates its effective shift detection ability and other important features. A practical application of the proposed method is demonstrated with the sensorless drive diagnosis case study.

Dr Chantelle May Clohessy (Meyer) is Head of Department and a senior lecturer in the Department of Statistics at the Nelson Mandela University. She completed her undergraduate with a BSc degree in Physics and Mathematical Statistics, and postgrad (Honours, Masters and PhD) in Mathematical Statistics. Her research focus is on renewable energy applications and statistical techniques used to assess these applications. She has knowledge in the fields of wind turbine noise, faults detection of solar panels, energy yield output estimation, solar resource forecasting, uncertainty assessments, statistical viability assessments of photovoltaic systems, machine learning, Bayesian statistics, linear models and experimental design. Dr Clohessy is Y2 NRF rated researcher and has held a NRF Thuthuka grant for 9 years. She has supervised more than 20 honours projects, 10 masters students and is currently completing supervision of her first Phd student. She has presented her research both internationally and nationally. She has also published her work in DHET accredited publications (10), with one paper having over 70 citations. She held the position of South African Statistical Association Secretary from 2017- 2022. Dr Clohessy is also a keen premier league hockey player where she has represented the province for various years and played recently for the EPCD team in 2024. She captained the South African Country and Districts team in 2016 and 2017 at two IPT tournaments. She is also the president of the Uitenhage hockey club.