As efforts associated with the exploration of multi-principal element alloys (MPEAs) using
computational and data-intensive methods continue to rise, experimental realization and …

Abstract Metal Additive Manufacturing (MAM) has transformed the manufacturing landscape,
bringing notable benefits such as intricate design capabilities, minimal material wastage …

A design optimization framework for process parameters of additive manufacturing based on
finite element simulation is proposed. The finite element method uses a coupled …

We present an efficient approach to quantify the uncertainties associated with the numerical
simulations of the laser‐based powder bed fusion of metals processes. Our study focuses on …

Generally, Medical Imaging Modalities (MIM) have a distinctive nature of low contrast,
complex background, and low resolution, containing burned-in textual data of patients. The …

Bayesian optimization is a stochastic, global black-box optimization algorithm. By combining
Machine Learning with decisionmaking, the algorithm can optimally utilize information …

Reactors are technical equipment enabling the conversion of reactants to products.
Commonly utilised in both chemical and biochemical industries, the prefix 'bio'distinguishes …

Product formulation is a complex and challenging process involving the careful balancing of
multiple factors to achieve the desired product characteristics. This chapter explores the data …

Machine Learning (ML) to engineering, in particular to process analysis, monitoring and
control, is often caused by the limited availability of suitable data and the cost of data …

Machine Learning (ML) to process analysis, monitoring and control is often caused by the
availability of suitable data and the cost of data acquisition. For many ML projects, datasets …