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Atiqur Rahman

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Open access Sep 2026

Selection of additive manufacturing process parameters by using ANOVA and regression analysis

The importance of additive manufacturing is increasing in day-to-day industrial applications due to its versatile uses. Process parameter selection is a tedious trial-and-error task. Supervised machine learning helps researchers use decision models to predict process parameters based on existing process data. The datas...

S. Saheb, Atiqur Rahman · 0 citations
Open access Aug 2026

A Transfer-Learning and Continuous Optimization-Based Framework for Predicting Heat Treatment-Dependent Mechanical Properties of DED-Processed Low-Alloy Steels

Directed energy deposition (DED) of low-alloy steels involves strongly coupled effects among alloy composition, solidification behavior, and post-deposition heat treatment, making mechanical property prediction difficult when target-domain data are limited. This study develops a transfer-learning and continuous optimiz...

Atiqur Rahman, Sung-Heng Wu, Ranjit Joy et al. · 0 citations

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