Earlycite

Research Article August 28 2026
A physics-guided unified damage index framework for explainable milling anomaly detection using interval-wise MTConnect multi-sensor fusion
Aswin Karkadakattil
Journal of Intelligent Manufacturing and Special Equipment (2026) https://doi.org/10.1108/JIMSE-05-2026-0020
View articletitled, A physics-guided unified damage index framework for explainable milling anomaly detection using interval-wise MTConnect multi-sensor fusion
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Literature Review July 30 2026
Deep learning-based detection of submerged debris and plastics in underwater environments: a systematic review
Sakeena Parveen; Abdullah Sardar
Journal of Intelligent Manufacturing and Special Equipment (2026) https://doi.org/10.1108/JIMSE-02-2026-0005
View articletitled, Deep learning-based detection of submerged debris and plastics in underwater environments: a systematic review
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Research Article July 28 2026
A quantitative ERP-driven framework for the circular economy: development and simulation-based validation for sustainable manufacturing
Elza Boutalbi; Khadidja Tahanout; Leila Zemmouchi-Ghomari
Journal of Intelligent Manufacturing and Special Equipment (2026) https://doi.org/10.1108/JIMSE-03-2026-0009
View articletitled, A quantitative ERP-driven framework for the circular economy: development and simulation-based validation for sustainable manufacturing
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Research Article July 15 2026
Physics-informed framework for long-term polymer degradation modeling
Aswin Karkadakattil
Journal of Intelligent Manufacturing and Special Equipment (2026) https://doi.org/10.1108/JIMSE-01-2026-0003
View articletitled, Physics-informed framework for long-term polymer degradation modeling
Supplementary data
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Research Article July 9 2026
Genetic algorithm–optimized loss balancing in physics-informed neural networks for manufacturing digital twin applications
Aswin Karkadakattil
Journal of Intelligent Manufacturing and Special Equipment (2026) https://doi.org/10.1108/JIMSE-04-2026-0016
View articletitled, Genetic algorithm–optimized loss balancing in physics-informed neural networks for manufacturing digital twin applications
Supplementary data
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