March 28, 2017 article Open access A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests Journal of Manufacturing Science and Engineering DOI: 10.1115/1.4036350 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 6 stored of 678 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Deep Learning Based Tool Wear Estimation Considering Cutting Conditions 2024 Procedia CIRP article Engineering Advanced machining processes and optimization Open access 11 citations Deep Learning Approach for Enhanced Transferability and Learning Capacity in Tool Wear Estimation 2024 Procedia CIRP article Engineering Advanced machining processes and optimization Open access 3 citations Digitalized manufacturing process sequences – foundations and analysis of the economic and ecological potential 2022 CIRP journal of manufacturing science and technology article Engineering Digital Transformation in Industry Open access 16 citations Optimisation of a Workpiece Clamping Position with Reinforcement Learning for Complex Milling Applications 2022 Lecture notes in computer science conference-paper Engineering Manufacturing Process and Optimization 2 citations Improving Build Quality in Laser Powder Bed Fusion Using High Dynamic Range Imaging and Model-Based Reinforcement Learning 2021 IEEE Access article Engineering Additive Manufacturing Materials and Processes Open access 72 citations Identifying and Analyzing Data Model Requirements and Technology Potentials of Machine Learning Systems in the Manufacturing Industry of the Future 2020 International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS) conference-paper Engineering Digital Transformation in Industry 7 citations 6 results References 0