Article
Engineering, Electrical & Electronic
Jing Wang, Xiaobin Cheng, Yan Gao, Xun Wang, Jun Yang
Summary: This article introduces the use of Ft-SNE for cutting condition monitoring, which can improve the performance of machine tool monitoring through optimization of classification performance and feature selection.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Manufacturing
J. Y. Oh, B. Sim, W. J. Lee, S. J. Choi, W. Lee
Summary: Feed rate is crucial for cutting force and cycle time. Optimized feed rate is determined based on a prediction model and algorithm to maintain cutting force, which is measured and adjusted in real-time. Experimental results prove that this feed rate optimization significantly reduces cycle time and maintains cutting force effectively.
JOURNAL OF MANUFACTURING PROCESSES
(2023)
Review
Automation & Control Systems
Sumanth Ratna Kandavalli, Aqib Mashood Khan, Asif Iqbal, Muhammad Jamil, Saqlain Abbas, Rashid Ali Laghari, Quentin Cheok
Summary: Measuring the response of different functional states of machines is essential for smooth production. An efficient measurement and control system helps detect failures. The concept of industry 5.0 has increased the importance of sensors in the industry, aiding the machining process and reducing failures. This paper reviews various sensors and their application in manufacturing processes, discussing advancements in quality measurement, cutting force measurement, and tool wear measurement. It also explores the adoption of IoT in machining processes and the improvement of sensor technology.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Automation & Control Systems
Gang Zhao, Kang Cheng, Wei Wang, Yazui Liu, Zhihua Dan
Summary: The application of the STEP-NC standard advances the CNC machining industry towards integration and automation. A model-based cutting tool selection method is proposed, which considers energy consumption as an evaluation factor and uses genetic algorithms for optimization. Experimental tests on typical parts validate the effectiveness and feasibility of this method.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Chemistry, Analytical
Ayman Mohamed, Mahmoud Hassan, Rachid M'Saoubi, Helmi Attia
Summary: This article reviews the latest technologies and components of TCM systems, with a focus on analyzing the advantages and limitations of wireless tool-embedded sensor nodes. It also provides a comprehensive review of dimensionality reduction techniques. Finally, it discusses attempts to generalize and enhance TCM systems and offers recommendations for future research directions.
Review
Engineering, Manufacturing
Quade Butler, Youssef Ziada, David Stephenson, S. Andrew Gadsden
Summary: This review outlines the techniques and methods for feed drive condition monitoring, diagnostics, and prognostics in recent research. It also describes commercial and industry solutions to Industry 4.0 condition monitoring.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2022)
Article
Engineering, Electrical & Electronic
Julio Garrido, Diego Silva, Juan Saez
Summary: This article proposes an extended STEP-NC model for stone cutting and demonstrates how modern technological resources can speed up the implementation of STEP-NC numerical controllers. Additionally, it suggests a mixed and flexible approach for machine automation based on STEP-NC, allowing different strategies to coexist during the execution of machining files.
Article
Engineering, Manufacturing
Jungsub Kim, Seungjoo Lee, Heebum Chun, ChaBum Lee
Summary: The study introduces a new type of dimensional sensor, CES, that can be used for spindle dynamic characterization and in-situ monitoring, unaffected by target surface curvature and lateral motion of the spindle.
JOURNAL OF MANUFACTURING PROCESSES
(2021)
Article
Computer Science, Artificial Intelligence
Lianyao Tang, Rong Chen
Summary: With the continuous development of the manufacturing industry, the application of NC machining technology has been expanded. However, the current methods for adjusting contour accuracy in NC machining are inefficient and heavily rely on manual experience. Therefore, an automatic compensation method based on fuzzy control is proposed to reduce contour error in NC machining.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Engineering, Industrial
Maximilian Benker, Michael F. Zaeh
Summary: Ball screw feed drives play a crucial role in machine tools, and monitoring their condition is essential. This paper presents a data-driven approach that can accurately assess the condition of unseen ball screws, providing a new method for monitoring the status of ball screw drives.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Industrial
Yaoke Wang, Ping Guo
Summary: This work presents a new optical design and machining strategy to achieve the one step generation of hierarchical optical structures on a flat surface for autostereoscopic effects. The design combines V-groove arrays as a parallax barrier for stereopsis and integrated diffraction gratings with variable grating spacing for motion parallax. Using tool geometry and elliptical tool vibration, the hierarchical structures are machined simultaneously to form V-grooves and generate blazed gratings. An autostereoscopic image with strong depth perception and high pixel density is fabricated.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
S. Ganesh Kumar, Bipin Kumar Singh, R. Suresh Kumar, Anandakumar Haldorai
Summary: A Digital Twin (DT) is a virtual representation of a product system that analyzes its functions and properties. DT has significant impacts in various fields by increasing productivity and reducing wastage. This article focuses on developing a DT model of a Lathe machine for Tool Condition Monitoring (TCM). Implementing DT in industries is challenging, especially when simulating online cutting forces and wear. While research on tool condition prediction using machine learning and Artificial Neural network models has been done, there is limited research on digital twins for TCM. This article provides a technique for implementing the DT model of a lathe tool and verifies its feasibility through a case study. The DT model is able to monitor and predict tool conditions, contributing to increased productivity and predictive maintenance in machining.
DEFENCE SCIENCE JOURNAL
(2023)
Article
Materials Science, Paper & Wood
Sasa Zivanovic, Zoran Dimic, Aleksandar Rakic, Nikola Slavkovic, Branko Kokotovic, Srecko Manasijevic
Summary: The paper proposes a programming methodology for advanced manufacturing based on STEP-NC. A virtual machine and a web interface are developed to program a CNC woodworking machining center. The developed methodology is validated through machining simulation and experiments.
WOOD MATERIAL SCIENCE & ENGINEERING
(2023)
Article
Engineering, Manufacturing
Sandro Turchetta, Luca Sorrentino, Gianluca Parodo
Summary: Diamond tools for natural stone processing are divided into cutting tools and surface machining tools, with diamond mills being commonly used in stone sawing processes. The performance and lifespan of diamond mills are influenced by factors such as material characteristics, working conditions, diamond segment production process, and diamond characteristics.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2022)
Article
Chemistry, Physical
Pawel Zawadzki, Rafal Talar, Adam Patalas, Stanislaw Legutko
Summary: This study investigates the impact of cutting angle, cutting depth, and cutting direction on cortical bone machining, and confirms that even negative cutting angles can guarantee controlled cutting and have wider applications in surgical procedures.
Article
Engineering, Industrial
Yu Zhang, Yongsheng Zhang, Kaiwen He, Dongsheng Li, Xun Xu, Yadong Gong
Summary: This paper presents an intelligent feature recognition method for STEP-NC-compliant manufacturing using artificial bee colony (ABC) algorithm and back propagation (BP) neural network. The method extracts geometric and topological information from STEP AP203 neutral file, constructs the minimum subgraphs of a part based on the concavity and convexity judgement algorithm, and proposes an improved BP neural network combined with ABC algorithm for STEP-NC-compliant manufacturing feature recognition. Case study concludes that the proposed method is effective and feasible.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Review
Engineering, Industrial
Chao Liu, Pai Zheng, Xun Xu
Summary: This paper presents a systematic literature review on the digitalisation and servitisation of machine tools in the context of Industry 4.0. The review provides a comprehensive understanding of recent advancements in this field, including key technologies, methods, standards, architectures, and applications. Additionally, a novel conceptual framework called Cyber-Physical Machine Tool (CPMT) is proposed as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. The paper also discusses major research issues, challenges, and future research directions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Qiunan Meng, Xun Xu
Summary: In this paper, an incomplete covering rough set method based on object similarity is proposed to derive a cover for attribute reduction. Experimental results show that it outperforms compared rough set in factor selection accuracy and quote prediction with various proportions of missing data.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Yu Zhang, Xian Yu, Jian Sun, Yongsheng Zhang, Xun Xu, Yadong Gong
Summary: This paper introduces an intelligent STEP-NC-compliant setup planning method that combines rules, AHP, and IBPNN, to automatically and reasonably optimize the machining sequence and datum decision of manufacturing feature groups. The proposed method is verified to be effective and feasible through a case study.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Industrial
Yuqian Lu, Hao Zheng, Saahil Chand, Wanqing Xia, Zengkun Liu, Xun Xu, Lihui Wang, Zhaojun Qin, Jinsong Bao
Summary: This position paper discusses the concept, needs, reference model, enabling technologies, and system frameworks of human-centric manufacturing. It provides a relatable vision and research agenda for future work in human-centric manufacturing systems. Human-centric manufacturing should address human needs and the human-machine relationships will evolve.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Industrial
Jie Bai, Shuiliang Fang, Xun Xu, Renzhong Tang
Summary: Cloud manufacturing aims to transform the manufacturing industry into a cloud-based service with efficient service standard expression, publication, collaboration, and sharing being a major challenge. To address this, the authors propose the concept of Bill Of Standard manufacturing Service (BOSS) and a synthesized algorithm called LMPF for quickly building a product-oriented BOSS tree.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Editorial Material
Engineering, Industrial
Jie Zhang, Junliang Wang, Ray Zhong, Weidong Li, Xun Xu, Bhaskaran Gopalakrishnan
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Editorial Material
Engineering, Industrial
Pai Zheng, Xun Xu, Lihui Wang
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Yaoyao Ping, Yongkui Liu, Lin Zhang, Lihui Wang, Xun Xu
Summary: Cloud manufacturing is a manufacturing model that provides on-demand manufacturing services to consumers. Scheduling is a crucial problem for cloud manufacturing, especially when dealing with multiple composite tasks. This research combines sequence generation algorithms with deep reinforcement learning to address cloud manufacturing scheduling problems.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Yongkui Liu, Yaoyao Ping, Lin Zhang, Lihui Wang, Xun Xu
Summary: Cloud manufacturing is a service-oriented manufacturing model that provides manufacturing resources as cloud services. This paper explores the use of Deep Reinforcement Learning (DRL) to solve scheduling issues in decentralized robot manufacturing services in cloud manufacturing, proposing DQN and DDQN-based scheduling algorithms. Results indicate that DDQN performs the best in terms of performance and indicators.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Law
Marwan Gharbia, Alice Chang-Richards, Xun Xu, Matilda Hook, Lars Stehn, Rene Jahne, Daniel Hall, Kenneth Park, Jingke Hong, Yingbin Feng
Summary: Through surveys conducted in several countries, this study found that self-certification by manufacturers is the main method of complying with building regulations when using off-site construction techniques. A regulatory compliance system that allocates risks and liabilities fairly is also important. Third-party certification and traceability are necessary for a functional regulatory system. The study recommends policymakers introduce changes in product standards and legislation to improve off-site construction's compliance and performance.
JOURNAL OF LEGAL AFFAIRS AND DISPUTE RESOLUTION IN ENGINEERING AND CONSTRUCTION
(2023)
Article
Engineering, Industrial
Pei Wang, Hai Qu, Qianle Zhang, Xun Xu, Sheng Yang
Summary: In this paper, a production quality prediction framework based on multi-task joint deep learning is proposed to simultaneously evaluate the multitask quality of all stages in a multistage manufacturing system. The proposed method outperforms traditional models in terms of R2, MAE, and RMSE, showing significant improvements in quality prediction accuracy.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Ahmed Z. Naser, Fantahun Defersha, Xun Xu, Sheng Yang
Summary: This paper explores the feasibility of predictive Life Cycle Assessment (LCA) for Additive Manufacturing (AM) by proposing a data-driven framework that combines Machine Learning (ML) and LCA. The framework is demonstrated through a case study on the Fused Filament Fabrication (FFF) process, achieving high prediction accuracy and good generalizability.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Kendrik Yan Hong Lim, Theresia Stefanny Yosal, Chun-Hsien Chen, Pai Zheng, Lihui Wang, Xun Xu
Summary: The increasing complexity of industrial systems requires more effective and intelligent maintenance approaches to address manufacturing defects. This paper introduces a cognitive digital twin system that leverages industrial knowledge graphs to support maintenance planning and operations. The system can manage interconnected systems, facilitate cross-domain analysis, and generate feasible solutions validated through simulation. It can also identify potential disruptions in new product designs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Anton Averyanov, Shohin Aheleroff, Jan Polzer, Xun Xu
Summary: The development of smart factories provides an incredible opportunity for the manufacturing industry to join Industry 4.0. Small businesses can stay competitive and be part of the Industry 4.0 era by digitally transforming conventional CNC machines at low cost to enable connectivity and efficient data communication with the machines.
