Research on Intelligent Manufacturing and Assembly https://www.syncsci.com/journal/RIMA <p><em><strong>Research on Intelligent Manufacturing and Assembly</strong></em> (RIMA) (eISSN: 2972-3329) is an international, peer-reviewed, open access journal dedicated to the latest advancements in intelligent manufacturing and assembly. RIMA serves as a critical bridge between cutting-edge research and practical applications, fostering collaboration between the academic community and industry practitioners. The journal aims to publish high-impact research that pushes the boundaries of knowledge in the design, analysis, manufacturing, and operation of intelligent systems and equipment. RIMA focuses on innovative technologies and methodologies that are transforming the manufacturing landscape, driving efficiency, precision, and sustainability in industrial processes. By publishing rigorous research and fostering a vibrant community of scholars and practitioners, RIMA aims to be the go-to resource for advancing the state-of-the-art in intelligent manufacturing and assembly.</p> <p>Topics of interest include, but are not limited to the following: <br>• Digital design and manufacturing <br>• Theories, methods, and systems for intelligent design <br>• Advanced processing techniques <br>• Modelling, control, optimization, and scheduling of systems <br>• Manufacturing system simulation and digital twin technology <br>• Industrial control systems and the industrial Internet of Things (IIoT) <br>• Safety and reliability assessment <br>• Robotics and automation <br>• Artificial intelligence and machine learning in manufacturing <br>• Supply chain optimization and management <br>• Additive manufacturing and materials science <br>• Cybersecurity and data privacy in manufacturing <br>• Sustainability and circular economy in manufacturing <br>• Bio-fabrication and other advanced manufacturing methods <br>• Digital Workforce and Automation <br>• <em>etc. </em></p> SyncSci Publishing Pte Ltd, Singapore en-US Research on Intelligent Manufacturing and Assembly 2972-3329 <p>Authors contributing to&nbsp;<em>Research on Intelligent Manufacturing and Assembly</em>&nbsp;agree to publish their articles under the&nbsp;<a href="http://creativecommons.org/licenses/by-nc/4.0">Creative Commons Attribution-Noncommercial 4.0 International License</a>, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit, that the work is not used for commercial purposes, and that in the event of reuse or distribution, the terms of this license are made clear.</p> Modeling & optimization of Ti6Al4V turning for sustainable shearing considering rake angle https://www.syncsci.com/journal/RIMA/article/view/RIMA.2024.01.004 <p>Titanium alloys, such as Ti6Al4V, have become increasingly prevalent in aerospace and biomedical industries owing to their exceptional mechanical properties and corrosion resistance. However, the machining of these alloys presents significant challenges including high tool wear, poor surface finish, and low productivity. This study focused on enhancing the machinability of Ti6Al4V during CNC turning using the Taguchi optimization method. This approach aims to identify the optimal cutting parameters that minimize the surface roughness, flank wear, and crater wear, thereby improving the overall machining performance. This study systematically investigated the influence of various cutting parameters on machining outcomes. The experimental results demonstrate that the Taguchi method effectively determines the optimal process parameters, leading to a significant reduction in surface roughness and tool wear. These findings highlight the potential of the Taguchi optimization technique for achieving improved machinability and sustainability in the machining of Ti6Al4V.</p> Amit Patil Sushil Ingle Copyright (c) 2024 Amit Patil, Sushil Ingle https://creativecommons.org/licenses/by-nc/4.0 2024-11-20 2024-11-20 3 1 118 128 10.25082/RIMA.2024.01.004 Formation of reflexive generative A.I. with ethical measures of use https://www.syncsci.com/journal/RIMA/article/view/RIMA.2024.01.003 <p>The application of reflexive generative AI in the social sphere will improve the quality of life of individuals and society. Its commercial application will require compliance with ethical standard measures to ensure that its use does not cause harm. The development, implementation and use of an ethical standard for the use of reflexive generative AI will increase the safety of its use. The ethical use of generative AI by individuals should be automatically regulated by it. The reflection of generative AI is implemented by the AGI multilogic and ensures the validity of content generation.</p> Evgeniy Bryndin Copyright (c) 2024 Evgeniy Bryndin https://creativecommons.org/licenses/by-nc/4.0 2024-11-01 2024-11-01 3 1 109 117 10.25082/RIMA.2024.01.003 Unleashing the potential of AI in modern healthcare: Machine learning algorithms and intelligent medical robots https://www.syncsci.com/journal/RIMA/article/view/RIMA.2024.01.002 <p>Artificial intelligence (AI) is playing an increasingly vital role in transforming the medical field, particularly in areas like medical imaging, clinical decision-making, pathology, and minimally invasive surgery. The rapid growth of medical data and the continuous refinement of machine learning algorithms have propelled AI's integration into healthcare. This study explores the advancements and applications of AI, specifically machine learning algorithms and intelligent medical robots, in enhancing diagnostics, treatment, and healthcare delivery. A comprehensive review of current AI applications in healthcare, including its use in medical imaging, pathology, clinical decision-making, and robotic-assisted surgery, was conducted. AI technologies such as the Da Vinci Surgical Robot and machine learning-based diagnostic tools have significantly improved diagnostic accuracy and the precision of minimally invasive surgeries. AI-driven systems also contributed to better clinical decision support, faster recovery times for patients, and more accurate treatment plans. Overall, AI, through machine learning algorithms and intelligent medical robots, is revolutionizing healthcare by offering promising improvements in diagnostics, surgical precision, and patient care.</p> Rizwan Ali Haiyan Cui Copyright (c) 2024 Rizwan Ali, Haiyan Cui https://creativecommons.org/licenses/by-nc/4.0 2024-10-22 2024-10-22 3 1 100 108 10.25082/RIMA.2024.01.002 Aspects of information and spiritual similarity of real and virtual spaces https://www.syncsci.com/journal/RIMA/article/view/RIMA.2024.01.001 <p>The results of numerous studies demonstrate the possibility of using the same approaches to studying real and virtual space in the context of their spatial perception. The study of virtual space can be carried out using the same parameters as physical space, and they should be considered equivalent. Virtual space is only one of the strategies for information copying of real space, the result of an irresistible human need to expand the horizons of research. Virtual space does not pose any threat to reality if we interpret the virtual environment as a transformation of the real environment, a new way of studying the mutual penetration of the virtual and real worlds. Learning to navigate in virtual space leads to safer life in real space.</p> Evgeniy Bryndin Copyright (c) 2024 Evgeniy Bryndin https://creativecommons.org/licenses/by-nc/4.0 2024-09-19 2024-09-19 3 1 94 99 10.25082/RIMA.2024.01.001