Article
Computer Science, Interdisciplinary Applications
Eduardo Harbs, Gabriel H. Negri, Guilherme Jarentchuk, Allan Y. Hasegawa, Roberto S. U. Rosso Jr, Marcelo da Silva Hounsell, Fernando H. Lafratta, Joao Carlos Ferreira
Summary: This paper presents a manufacturing system compliant to IEC 61499 and STEP-NC standards, integrating them to meet the requirements of interoperability and flexibility. Through the development and experimentation of a system named CNC-C-2, unprecedented interoperability and flexibility were achieved, showing the potential of compliance to Function Blocks and STEP-NC standards.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2021)
Article
Engineering, Industrial
Mohammad Givehchi, Yongkui Liu, Xi Vincent Wang, Lihui Wang
Summary: Due to uncertainties and collaborations, manufacturing systems are demanded to be agile, adaptive, flexible and interoperable. Process planning systems are crucial in small and medium-sized machining job shops. Cloud-based adaptive distributed process planning offers an effective approach to enhance agility, adaptability, flexibility and interoperability of manufacturing systems.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Automation & Control Systems
Liliya Martinova, Nikolay Kozak, Ilya A. Kovalev, Aleksandr B. Ljubimov
Summary: The article proposes a model of the components of the subsystem for evaluating and monitoring the health of a CNC machine, which allows for making decisions in a timely manner to maintain machine operability, using information obtained at different stages.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Yuanyuan Zhao, Quan Liu, Wenjun Xu, Huiqun Yuan, Ping Lou
Summary: This paper introduces a self-learning method to explore correlations from STEP-NC process planning documents to obtain machining knowledge in order to enhance the comprehensiveness of the ontology model. By combining the Apriori algorithm and Map/Reduce framework, the method successfully embeds the mined results into the model, effectively improving the model's suitability for information integration and industrial applications.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
Article
Engineering, Electrical & Electronic
Tim von Hahn, Chris K. Mechefske
Summary: This article demonstrates several best practices and challenges discovered while building an ML system to detect tool wear in metal CNC machining. By optimizing data infrastructure, starting with simple models, being aware of data leakage, using open-source software, and leveraging advances in computational power, a deployable ML system is achieved in a real-world manufacturing environment.
Article
Automation & Control Systems
Georgi M. Martinov, Sergey V. Sokolov, Liliya I. Martinova
Summary: This paper proposes an approach for a gradual transition to cloud-based technologies in machine-building shop floors. It suggests using third-party and personal cloud services, along with the digital shadow of CNC machines and the OPC UA standard, to create a unified information space. The application of this approach covers the entire product lifecycle interval, from design and development of manufacturing technology to production and storage of information related to the machining process.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Paulo Ricardo Marques de Araujo, Romulo Goncalves Lins
Summary: This paper presents a cloud-based approach of an automatic system based on stereo vision and image analysis for automating workpiece referencing in machining companies. Experimental results validate the application of the proposed architecture in a real machining process.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Engineering, Mechanical
Wangqiang Xiao, Zhanhao Xu, Hechuan Bian, Zhongkai Li
Summary: This study proposed a lightweight design method for CNC machine tools based on particle damping technology, which effectively reduced vibration intensity by optimizing wall thickness and analyzing dynamic characteristics. Experimental results showed that the vibration amplitudes of lightweight CNC machine tools significantly decreased, demonstrating better performance.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Maznah Iliyas Ahmad, Yusri Yusof, Mohammad Sukri Mustapa, Mohd Elias Daud, Kamran Latif, Aini Zuhra Abdul Kadir, Yazid Saif, Anbia Adam, Noor Hatem
Summary: This article proposes an integrated monitoring system for milling process, which bridges the gap between physical and cyber-physical systems through software applications. The system is validated through two case studies and it is proven to be highly sensitive to the condition of cutting tools.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Zhiming Feng, Xinglong Min, Wei Jiang, Fan Song, Xueqin Li
Summary: This paper analyzes several methods related to thermal error modeling in the latest research applications, summarizes their deficiencies, and proposes a thermal error modeling method of CNC machine tool based on the improved particle swarm optimization (PSO) algorithm and radial basis function (RBF) neural network, named as IPSO-RBFNN. By introducing a compression factor to make the PSO algorithm balance between global and local search, the structure parameters of RBF neural network are optimized. The IPSO-RBFNN method is adopted to establish the thermal error model for CNC machine tool, achieving a predictive accuracy of 2.05 mu m in Z direction.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Lirong Zhou, Fangyi Li, Yue Wang, Liming Wang, Geng Wang
Summary: This paper investigates the modeling of standby and auxiliary power of machine tools and proposes a new model. Experimental results confirm that the new model is closer to the actual measurement curve, avoiding prediction errors of standby energy consumption, and theoretical and empirical power equations for auxiliary components are derived.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Review
Engineering, Manufacturing
Li-Chih Wang, Kung-Ming Lan, Kang-Chu Fan
Summary: This paper introduces the application of cloud-based supervisory control and data acquisition (SCADA) system in the manufacturing industry and its impact on medium-sized manufacturing enterprises. The paper demonstrates the feasibility and advantages of developing a cloud-based intelligent machine monitoring and control system (CIM-MCS) framework and deploying it on a public cloud platform.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2023)
Review
Automation & Control Systems
Rasoul Rashidifar, Hamed Bouzary, F. Frank Chen
Summary: This paper discusses the problem of cloud-based resource scheduling through a literature review, identifying existing gaps and recommending potential paths for future researchers. The findings of the review show that time and cost are the most focused objective functions in resource scheduling, and metaheuristic algorithms are widely used.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Longfei Zhou, Lin Zhang, Berthold K. P. Horn
Summary: Efficient service scheduling is crucial for supporting collaborative manufacturing platforms such as IoT-enable manufacturing systems and cloud manufacturing. This paper proposes a collaborative optimization algorithm COOPS for simultaneous scheduling of processing tasks and logistics tasks in cloud manufacturing, showing shorter average completion time for all tasks in different scenarios compared to typical optimization algorithms.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Automation & Control Systems
Mingyi Guo, Xifeng Fang, Zhongtai Hu, Qun Li
Summary: This paper focuses on common problems in the manufacturing of numerical control machine tools and proposes a new system architecture using digital twin technology to solve these problems. The improved algorithm allows for more accurate detection of collision information between tools and machine tools, and the display of more realistic workpiece shapes. Furthermore, online tool wear monitoring can be achieved through model synchronous motion driven by production perception data.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Endocrinology & Metabolism
Denise Machado Mourao, Bruna Martins Grassi Sedlmaier, Victor Luiz Rocha Pires, Grasiely Faccin Borges
Summary: Educational intervention about diabetes for students and school staff in Brazil is effective in improving knowledge and perception of this condition.
INTERNATIONAL JOURNAL OF DIABETES IN DEVELOPING COUNTRIES
(2023)
Article
Computer Science, Interdisciplinary Applications
D. Mourtzis, J. Angelopoulos, N. Panopoulos
Summary: In the realm of the fourth industrial revolution, ensuring the flawless and continuous operation of technology-rich workplaces is a challenging problem. This paper presents a tool based on intelligent decision making and augmented reality (AR) to assess technician skills, allocate jobs, and provide task-related support. The framework is validated in a real industrial case study of a CNC machine manufacturer.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Automation & Control Systems
Panagiotis Stavropoulos, Thanassis Souflas, Christos Papaioannou, Harry Bikas, Dimitris Mourtzis
Summary: Chatter is a major limitation in milling processes, affecting surface quality and machine tool health. Existing detection methods lack adaptability and may be overfit. This study proposes a vibration-based detection method with high classification performance and fast detection speed.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Review
Chemistry, Multidisciplinary
Panagiotis Stavropoulos, Alexios Papacharalampopoulos, Kyriakos Sabatakakis, Dimitris Mourtzis
Summary: The automation of workflows for the optimization of manufacturing processes through digital twins is achievable with the matured technologies of Industry 4.0. However, there is potential for further exploration of technologies like metamodelling languages. A framework utilizing an automation workflow knowledge database, technology classification, and metamodelling language is presented, highlighting its usefulness in creating digital twins for manufacturing processes while involving human input. Two process control paradigms are used to illustrate the applicability of the approach within the framework of certifiable human-in-the-loop process optimization.
APPLIED SCIENCES-BASEL
(2023)
Review
Chemistry, Multidisciplinary
Dimitris Mourtzis, John Angelopoulos, Nikos Panopoulos
Summary: Blockchain is a distributed and decentralized database that allows for secure sharing of information among computer network nodes. In the context of Industry 4.0, digitalization of manufacturing systems has increased the importance of big data sets, but also heightened the risk of cyberattacks. Blockchain technology contributes to intelligent manufacturing by protecting data validity, facilitating inter- and intra-organizational communication, and improving manufacturing processes' efficiency.
APPLIED SCIENCES-BASEL
(2023)
Review
Chemistry, Analytical
Amy Grech, Jorn Mehnen, Andrew Wodehouse
Summary: This research explores the link between virtual reality and artificial intelligence technologies and product ideation in order to assist and enhance creative scenarios in the engineering field. A bibliographic analysis and technology review are performed to address current challenges in group ideation and apply this knowledge to transform current ideation scenarios into a virtual environment. Through intelligent team moderation, enhanced communication techniques, and multi-sensory stimuli, brainstorming activities are enhanced, providing a platform for future research into Industry 5.0 and smart product development.
Editorial Material
Chemistry, Analytical
Nikolaos Tapoglou
Article
Computer Science, Information Systems
Dimitris Mourtzis, Sofia Tsoubou, John Angelopoulos
Summary: Robotic systems have become essential in modern manufacturing due to their unique characteristics. However, their low reliability poses challenges and affects productivity and profit. To address this issue, this research proposes a method based on digital twin and predictive maintenance to optimize the reliability of a robotic cell. The study includes simulation, machine learning model training for fault detection, and a framework for predicting remaining useful life. Applying appropriate maintenance tasks based on these results can prevent serious failures and ensure high reliability.
Review
Computer Science, Information Systems
Dimitris Mourtzis, John Angelopoulos, Nikos Panopoulos
Summary: This paper aims to identify the capabilities and distinguishing characteristics of both humans and machines, laying the groundwork for improving human-machine interaction (HMI), emphasizing the concept of a Humachine.
Article
Engineering, Industrial
Dimitris Mourtzis, John Angelopoulos, Nikos Panopoulos
Summary: With the advances in Industry 4.0 and the upcoming Industry 5.0, the use of multiple UAVs for indoor tasks has increased. The proposed method in this paper presents a way to remotely plan and control drones based on the use of Augmented Reality. This method contributes towards enabling engineers to visualize the drone path and add multiple waypoints without human intervention.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Mechanical
Leon Proud, Nikolaos Tapoglou, Krystian K. Wika, Chris M. Taylor, Tom Slatter
Summary: Due to their high hardness, osseointegration and low chemical reactivity, titanium alloys have become an invaluable material for medical applications. However, these same properties also contribute to difficulties in machining, including tool wear and surface quality. This study explores the use of a novel external supercritical CO2 coolant strategy to minimize tool wear during milling of grade 2 titanium, and concludes that combining this coolant with minimum quantity lubrication can significantly increase tool life.
Article
Engineering, Electrical & Electronic
Dimitris Mourtzis, John Angelopoulos
Summary: Climate change, energy efficiency, and access to contemporary energy services are important global topics. The establishment of reliable communication infrastructure and increased digitization has led to the creation of smart grids. Reactive power optimization, using algorithms like particle swarm optimization, is crucial for energy production and distribution. However, premature convergence and local optima can be issues with these algorithms. This research presents an improved PSO algorithm for minimizing power loss in smart grids, achieving approximately an 11% improvement compared to conventional algorithms, as demonstrated on the IEEE 30-bus standardized model.
Article
Engineering, Electrical & Electronic
Chara Efstathiou, Ioanna Tsormpatzoglou, Nikolaos Tapoglou
Summary: This study introduces the Curvic3D kinematic model, which accurately determines the geometry of a curvic coupling using a CAD system. The model allows for the customization and parametrization of the coupling design, and a finite element analysis is conducted to analyze the behavior of the coupling under different loading conditions. The study finds that various geometric parameters have a significant impact on the load-carrying capacity of the curvic coupling.
Proceedings Paper
Engineering, Multidisciplinary
Dimitris Mourtzis, Panagiotis Kaimasidis, John Angelopoulos, Nikos Panopoulos
Summary: Traditional manufacturing systems rely on CNC for product and component manufacturing, requiring skilled personnel. Industry 4.0 introduces advanced digital technologies like XR, including AR, MR, and VR, to improve user perception and enable extended HMI. This research presents a framework using AR to facilitate engineers in generating Gcode scripts for machining operations, with MR providing a better perception of processes and virtual instructions for operators, and Cloud-based communication for automated transmission of Gcode to machine tools.
PRODUCT LIFECYCLE MANAGEMENT PLM IN TRANSITION TIMES: THE PLACE OF HUMANS AND TRANSFORMATIVE TECHNOLOGIES, PLM 2022
(2023)
Review
Engineering, Industrial
Jiewu Leng, Yuanwei Zhong, Zisheng Lin, Kailin Xu, Dimitris Mourtzis, Xueliang Zhou, Pai Zheng, Qiang Liu, J. Leon Zhao, Weiming Shen
Summary: Manufacturers are realizing the importance of system resilience and considering the use of Decentralized Autonomous Organization (DAO) to achieve decentralized autonomous manufacturing and resilient Industry 5.0 vision. This paper reviews the literature on Decentralized Manufacturing (DM) and Autonomous Manufacturing (AM), and proposes a manufacturing paradigm called Decentralized Autonomous Manufacturing (DAM). Future research directions and challenges of DAM are highlighted.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
