Journal of Manufacturing and Materials Processing | Selected Papers on Intelligent Manufacturing in 2021–2022

1. “Digital Twins for High-Tech Machining Applications—A Model-Based Analytics-Ready Approach”
by Albrecht Hänel, André Seidel, Uwe Frieß, Uwe Teicher, Hajo Wiemer, Dongqian Wang, Eric Wenkler, Lars Penter, Arvid Hellmich and Steffen Ihlenfeldt
J. Manuf. Mater. Process. 2021, 5(3), 80; https://doi.org/10.3390/jmmp5030080
Available online: https://www.mdpi.com/2504-4494/5/3/80

2. “3D Printing of Biomass–Fungi Composite Material: Effects of Mixture Composition on Print Quality”by Abhinav Bhardwaj, Al Mazedur Rahman, Xingjian Wei, Zhijian Pei, David Truong, Matt Lucht and Na Zou
J. Manuf. Mater. Process. 2021, 5(4), 112; https://doi.org/10.3390/jmmp5040112
Available online: https://www.mdpi.com/2504-4494/5/4/112

3. “Modelling and Optimization of Machining of Ti-6Al-4V Titanium Alloy Using Machine Learning and Design of Experiments Methods”
by José Outeiro, Wenyu Cheng, Francisco Chinesta and Amine Ammar
J. Manuf. Mater. Process. 2022, 6(3), 58; https://doi.org/10.3390/jmmp6030058
Available online: https://www.mdpi.com/2504-4494/6/3/58

4. “Flange Wrinkling in Deep-Drawing: Experiments, Simulations and a Reduced-Order Model”
by Kelin Chen, Adrian J. Carter and Yannis P. Korkolis
J. Manuf. Mater. Process. 2022, 6(4), 76; https://doi.org/10.3390/jmmp6040076
Available online: https://www.mdpi.com/2504-4494/6/4/76

5. “Wind Tunnel Experiments on an Aircraft Model Fabricated Using a 3D Printing Technique”
by Katarzyna Szwedziak, Tomasz Łusiak, Robert Bąbel, Przemysław Winiarski, Sebastian Podsędek, Petr Doležal and Gniewko Niedbała
J. Manuf. Mater. Process. 2022, 6(1), 12; https://doi.org/10.3390/jmmp6010012
Available online: https://www.mdpi.com/2504-4494/6/1/12

6. “A Novel Approach for Real-Time Quality Monitoring in Machining of Aerospace Alloy through Acoustic Emission Signal Transformation for DNN”
by David Adeniji, Kyle Oligee and Julius Schoop
J. Manuf. Mater. Process. 2022, 6(1), 18; https://doi.org/10.3390/jmmp6010018
Available online: http://www.mdpi.com/2504-4494/6/1/18

7. “Causal Discovery in Manufacturing: A Structured Literature Review”
by Matej Vuković and Stefan Thalmann
J. Manuf. Mater. Process. 2022, 6(1), 10; https://doi.org/10.3390/jmmp6010010
Available online: http://www.mdpi.com/2504-4494/6/1/10

8. “Physics-Based Simulations of Chip Flow over Micro-Textured Cutting Tool in Orthogonal Cutting of Alloy Steel”
by Kaushalendra V. Patel, Krzysztof Jarosz and Tuğrul Özel
J. Manuf. Mater. Process. 2021, 5(3), 65; https://doi.org/10.3390/jmmp5030065
Available online: http://www.mdpi.com/2504-4494/5/3/65

9. “Top Surface Roughness Modeling for Robotic Wire Arc Additive Manufacturing”
by Heping Chen, Ahmed Yaseer and Yuming Zhang
J. Manuf. Mater. Process. 2022, 6(2), 39; https://doi.org/10.3390/jmmp6020039
Available online: http://www.mdpi.com/2504-4494/6/2/39

10. “Prediction of Machining Condition Using Time Series Imaging and Deep Learning in Slot Milling of Titanium Alloy”
by Faramarz Hojati, Bahman Azarhoushang, Amir Daneshi and Rostam Hajyaghaee Khiabani
J. Manuf. Mater. Process. 2022, 6(6), 145; https://doi.org/10.3390/jmmp6060145
Available online: http://www.mdpi.com/2504-4494/6/6/145