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Implementing machine learning in robotic wire arc additive manufacturing for minimizing surface roughness Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-03-16 Kashif Hasan Kazmi, Mukesh Chandra, Sonu Rajak, Sumit K. Sharma, Amitava Mandal, Alok Kumar Das
Wire arc additive manufacturing (WAAM) has emerged as an important type of metal additive manufacturing technique in recent years. The most critical challenge in WAAM is to achieve the desired surf...
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AR-assisted assembly method based on instance segmentation Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-03-16 Chaofan Lv, Bo Liu, Dianliang Wu, Jianhao Lv, Jianjun Li, Jinsong Bao
AR-assisted assembly refers to the overlaying of virtual models, annotations, and other AR instructions in a genuine scene to help workers perform assembly tasks. However, most AR-aided assembly pr...
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Digital twin-enhanced laser cutting production system design and operation Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-03-15 Zhuorui Fu, Ning Zhao, Lei Luo
The design and operation of laser cutting production systems (LCPS) are critical for reducing cost and improving efficiency. In this study, a digital twin (DT) approach for the LCPS is proposed to ...
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Synthetic data generation for digital twins: enabling production systems analysis in the absence of data Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-03-13 Paulo Victor Lopes, Leonardo Silveira, Roberto Douglas Guimaraes Aquino, Carlos Henrique Ribeiro, Anders Skoogh, Filipe Alves Neto Verri
Industry increasingly focuses on data-driven digital twins of production lines, especially for planning, controlling and optimising applications. However, the lack of open data on manufacturing sys...
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The role of tool path on microstructure uniformity in large-format additive manufacturing: integrated thermo-metallurgical-mechanical approach Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-03-04 Jakub Mikula, Rajeev Ahluwalia, Athanasius Louis Commillus, Kai Ren, Youxiang Chew, Guglielmo Vastola, Yong-Wei Zhang
Directed energy deposition (DED) of large metal components has clear potential to revolutionise supply chains in several sectors, including marine & offshore and oil & gas. To insert this technolog...
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Evaluation method for the impact of digital finance on the environmental performance of manufacturing industry Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-03-04 Hongjuan Li
A new evaluation method for the impact of digital finance on the environmental performance of the manufacturing industry is proposed to improve the accuracy of evaluation results and provide reliab...
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Investigation on the effect of corner error in WEDM taper cutting process of Ti–6Al–4V Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-26 Ömer Bayraktar, Muhammed Furkan Erhan
Wire Electrical Discharge Machining (WEDM) is a non-conventional manufacturing method known for producing high-quality surface finishes and relies on the condition that materials conduct electricit...
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(DT4Smart) discrete event simulation and Digital Twins in warehouse logistics: a bibliometric and content analysis-based systematic literature review Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-25 Eleni Aretoulaki, Stavros T. Ponis, George Plakas, Dimitra Tzanetou
In Warehouse Logistics (WL), the growing adoption of Industry 4.0 automations coupled with the demand for efficient and almost instantly responsive decision-making has already created a paradigm sh...
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Optimization of product design process in cloud manufacturing system based on swarm intelligence Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-25 Xianru Shang, Zijian Liu, Chen Gong
Currently, manufacturing industries in many countries are grappling with an imbalance in the supply and demand of manufacturing resources, encompassing resource scarcity and idleness, as well as in...
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Toward cyber-physical systems for monitoring and analyzing energy consumption of machine tools Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-23 Hyoung Seok Kang, Ju Yeon Lee
This paper presents a digital twin and cyber-physical systems (CPS) environment for monitoring and analyzing the energy consumption of machine tools. Machine tools, which account for a large portio...
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Quality control in manufacturing – review and challenges on robotic applications Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-22 A. Papavasileiou, G. Michalos, S. Makris
Quality control methods and techniques have been investigated in different fields of manufacturing during the last decades. The introduction of robots in manufacturing processes has created a rapid...
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Correction Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-22
Published in International Journal of Computer Integrated Manufacturing (Ahead of Print, 2024)
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Production digital twin: a systematic literature review of challenges Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-21 Slimane Kerrouchi, El-Houssaine Aghezzaf, Johannes Cottyn
The manufacturing industry is entering the fourth industrial revolution, which aims to shift the manufacturing paradigm to data-driven smart manufacturing. Many barriers still limit the adoption of...
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Research on data security in industry 4.0 manufacturing industry against the background of privacy protection challenges Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-21 Zeyu Tang, Chang Zeng, Yali Zeng
As the manufacturing industry advances into the era of Industry 4.0, data security has emerged as a critical concern in the face of growing privacy protection challenges. This research paper explor...
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Automatic computation of bending sequences for double-head wire bending machines Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-20 Andrea Baraldo, Luca Bascetta, Fabrizio Caprotti, Sumit Chourasiya, Gianni Ferretti, Angelo Ponti, Basak Sakcak
Determining a feasible bending sequence for a double-head bending machine is a challenging and time-consuming task, even for an expert operator. An automatic bending sequence computation algorithm ...
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An analysis of heat source contribution and design of optimal cooling method for ball screw feed system Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-19 Huayang Wu, Jiejing Li, Haixu Liu, Dunwen Zuo
Fundamentally, the heat source in the ball screw feed system accounts for the thermal behavior of ball screw. Due to the fact that cooling resources are not always sufficient, the main objective of...
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A low-cost vision-based weld-line detection and measurement technique for robotic welding Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-18 Janvita Reddy, Ananta Dutta, Avishek Mukherjee, Surjya K Pal
To make robotic welding more flexible and intelligent, artificial intelligence-based systems are one of the most important developments. This paper introduces a computer vision-based algorithm for ...
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Web-based simulation and motion planning for human-robot and multi-robot applications Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-16 Tudor B. Ionescu
This paper introduces the human-robot and multi-robot programming and simulation capabilities of a web-based, open-source robot programming and simulation tool called Assembly. The tool supports sc...
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Digital twin-based reinforcement learning framework: application to autonomous mobile robot dispatching Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-15 Amel Jaoua, Samar Masmoudi, Elisa Negri
This paper proposes a new framework for embedding an Intelligent Digital Twin (DT) in a production system with the objective of achieving more efficient real-time production planning and control. F...
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Effective integration of low-cost digital manufacturing systems: a reference architecture driven approach Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-11 J. Kaiser, G. Hawkridge, D. McFarlane, F. Schnicke, K. Kruger
Integration involves the systematic linking of system components, functions and solutions. For digital systems comprising low-cost components, integration enables the sharing of resources and allow...
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Manufacturing cloud service recommendation model based on deep feature learning and user preference perception Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-11 Shenquan Huang, Yujie Wang, An Long, Xiaohui Zhu, Luchuan Yu
The manufacturing cloud service recommendation model is a key technology for users to quickly discover and obtain the personalized services they need from the increasingly expanding manufacturing c...
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A comparative study for the assessment of marker-less mixed reality applications for the operator training Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-02-06 Agnese Brunzini, Marianna Ciccarelli, Mikhailo Sartini, Alessandra Papetti, Michele Germani
With the rising concept of Industry 5.0, the worker’s needs and well-being are placed at the center of the production process. The use of extended reality can be exploited to provide the operator w...
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Smart manufacturing enabled by intelligent technologies Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-01-18 Yuqian Lu, Lihui Wang, Aydin Nassehi, Jiafu Wan
Published in International Journal of Computer Integrated Manufacturing (Vol. 37, No. 1-2, 2024)
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A systematic investigation of the barriers to effective implementation of human-robot assembly line: an integrated multi-criteria decision-making approach Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-01-18 Bo Tian, Mukund Janardhanan, Marina Marinelli
Human-robot collaboration (HRC) is putting humans back at the centre of manufacturing via tech-empowered workers. On human-robot assembly line (HRAL), humans and collaborative robots (cobots) can p...
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GNN-based deep reinforcement learning for MBD product model recommendation Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-01-18 Yuying Hu, Zewen Sheng, Min Ye, Meiyu Zhang, Chengfeng Jian
Digital twin is more and more widely used, and the delivery demand of digital twin is more and more prominent at the same time of product physical delivery. Research on the digital twin product mod...
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Smart manufacturing under limited and heterogeneous data: a sim-to-real transfer learning with convolutional variational autoencoder in thermoforming Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2024-01-18 Milad Ramezankhani, Mehrtash Harandi, Rudolf Seethaler, Abbas S. Milani
Data in advanced manufacturing are often sparse and collected from various sensory devices in a heterogeneous and multi-modal fashion. Thus, for such intricate input spaces, learning robust and rel...
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Quantum machine learning a new frontier in smart manufacturing: a systematic literature review from period 1995 to 2021 Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-20 Vaibhav S. Narwane, Angappa Gunasekaran, Bhaskar B. Gardas, Pinyarat Sirisomboonsuk
Quantum machine learning can play an essential role in smart manufacturing applications. This paper aimed to understand the state of the art of quantum computing in machine learning and its role in...
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Adaptive radial basis function neural network sliding mode control of robot manipulator based on improved genetic algorithm Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-19 Hang Li, Xiaobing Hu, Xuejian Zhang, Haijun Chen, Yunchen Li
Since the trajectory-tracking control performance of multi-joint robot manipulator may be degraded due to modeling errors and external disturbances, this paper designs a new adaptive robot manipula...
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Digital twin and parameter correlation-enabled variant design of production lines Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-22 Douxi Yan, Jiafeng Yang, Xiaofeng Zhu, Jiewu Leng, Ding Zhang, Yuqian Lu, Qiang Liu
The rapid transformation of production lines into a new design scheme is the key to improving the market competitiveness of enterprises. The production line is a complex manufacturing system with a...
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Multi-agent modelling of cyber-physical systems for IEC 61499-based distributed intelligent automation Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-21 Guolin Lyu, Robert W. Brennan
Traditional industrial automation systems developed under centralized architectures are statically programmed with determined procedures to perform predefined tasks in structured environments. The ...
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A multi-input parallel convolutional attention network for tool wear monitoring Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-20 Qiang Liu, Dingkun Li, Jing Ma, Xudong Wei, Zhengyan Bai
Effective tool wear monitoring is of great importance for machining process. With existing deep learning-based methods, the end-to-end model is often combined with sensor data to predict the state ...
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A recycling model based on blockchain and reverse logistics for remanufacturing Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-17 Yanhong Wang, Shuqiao Dai, Zhigang Jiang, Qingshan Gong
This paper addresses the challenge of integrating discarded products as pivotal raw materials in the remanufacturing process. The pervasive lack of transparency in the origin of discarded products ...
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An AutomationML extension towards interoperability of 3D virtual commissioning software applications Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-15 Jiaqi Zhao, El-Houssaine Aghezzaf, Johannes Cottyn
To achieve interoperability between different 3D virtual commissioning software, a generic virtual commissioning data model is required. AutomationML is a standard neutral format for interoperabili...
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Digital twin-driven parameter change propagation path optimization for production line variant design Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-17 Douxi Yan, Jiafeng Yang, Ding Zhang, Jiewu Leng, Qiang Liu
Current mass individualization requires that production lines for processing products be able to quickly vary to adapt to product changes. The variation and propagation of parameters have a central...
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Special issue “Towards Digitalized Manufacturing 4.0” Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-12-12 Dimitris Mourtzis
Published in International Journal of Computer Integrated Manufacturing (Vol. 36, No. 12, 2023)
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An intelligent recommender system for tool selection in conventional machining Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-11-20 Bilal Muhammed, P. Srimannarayana, Prasenjit Das, B. P. Gautham
Cutting tool manufacturers face a tough challenge in developing custom solutions for specific customer requirements. Several trials are required, encompassing the selection of materials, tool confi...
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Skills for Industry 4.0: a structured repository grounded on a generalized enterprise reference architecture and methodology-based framework Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-11-14 Marta Pinzone, Paola Fantini, Marco Taisch
This paper outlines a conceptual framework and a repository of skills for Industry 4.0 that manufacturing managers and other stakeholders can use for training, hiring and developing human resources...
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Virtual prototyping for the textile industry: a framework supporting the production of crocheted objects Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-11-11 Alberto Cannavò, Massimo Gismondi, Fabrizio Lamberti
Over the last years, many progresses have been made in the field of virtual prototyping, pushed by the interest of industries and artisans. Especially in the context of the textile industry, the di...
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Extending factory digital Twins through human characterisation in Asset Administration Shell Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-11-11 Vincenzo Cutrona, Niko Bonomi, Elias Montini, Tamas Ruppert, Giacomo Delinavelli, Paolo Pedrazzoli
This paper extends the traditional factory digital twins by incorporating human characterisation in Asset Administration Shell (AAS). The extension lays the basis for human-centred control and mana...
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(DT4Smart) a digital twin-based modularized design approach for smart warehouses Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-11-05 Zhenyong Wu, Rong Zhou, Mark Goh, Yuan Wang, Zhitao Xu, Wenyan Song
The rapid emergence and widespread adoption of next-generation information technologies have led to a growing recognition of the need for digitalized warehouse designs. However, creating a digital ...
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Temperature monitoring system of friction stir welding based on digital twin Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-11-05 Xiaohong Lu, Zhuo Sun, Yihan Luan, Le Teng, Steven Y. Liang
Temperature field distribution of friction stir welding (FSW) influences weld quality directly, so real-time monitoring of the welding temperature is significant. However, it is difficult to monito...
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Quality–efficiency coupling prediction and monitoring-based process optimization of thin plate parts with multi-machining feature Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-10-16 Pei Wang, Fanhui Bu, Xianguang Kong, Jiantao Chang, Yixin Cui, Anji Zhang
Quality and efficiency prediction, as well as coupling optimization, is very important for improving product production. However, most of the researches are studying the quality and efficiency sepa...
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Correction Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-10-09
Published in International Journal of Computer Integrated Manufacturing (Ahead of Print, 2023)
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An application-oriented digital twin framework and the multi-model fusion mechanism Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-10-05 Qing Zheng, Guofu Ding, Haizhu Zhang, Kai Zhang, Shengfeng Qin, Shuying Wang, Wenpei Huang, Qifeng Liu
The digital twin (DT) technology facilitates the complete lifecycle management of equipment by integrating physical and virtual spaces through data mapping. Many narrative DT frameworks and modelin...
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A machining error tracing method based on MEA-BP neural network for quality improvement of gear hubs Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-10-04 Yongsheng Liu, Xinhui Zhang, Kai Ding, Jizhuang Hui, Jin Zhao, Felix T.S. Chan
The machining quality of workpieces is greatly influenced by the performance of an equipment. Furthermore, it is difficult to establish an error tracing model with high tracing accuracy using a mat...
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Digital twins in product-service lifecycles: a framework proposal for enhancing competitiveness and sustainability in manufacturing business Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-10-05 Mira Timperi, Kirsi Kokkonen, Lea Hannola
Manufacturing companies have shifted their interest toward comprehensive solutions and novel digital technologies. These technologies, such as digital twins (DTs), have enabled new business opportu...
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Data-driven surrogate modelling of residual stresses in Laser Powder-Bed Fusion Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-10-04 L. Lestandi, J.C. Wong, G.Y. Dong, S. J. Kuehsamy, J. Mikula, G. Vastola, U. Kizhakkinan, C.S. Ford, D.W. Rosen, M.H. Dao, M.H. Jhon
In order to enable the industrialization of additive manufacturing, it is necessary to develop process simulation models that can rapidly predict part quality. Although multi-physics simulations ha...
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Working with collaborative robots and its influence on levels of working stress Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-30 Miguel A. Mariscal, Sergio Ortiz Barcina, Susana García Herrero, Eva María López Perea
The use and the rapid growth of the cobot in industry are changing working conditions. New jobs can imply new advantages and inconveniences, which call for new occupational risk assessments. The ai...
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Solid modelling approach for 3D tolerance analysis of linear dimension applied to planar faces in an assembly Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-25 Nejah Tounsi, Borhen Louhichi
This paper presents a 3D tolerance analysis approach for linear dimensions applied to planar faces in an assembly. The assembly variations are generated and visualized as an explicit geometrical st...
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Unlocking factors of digital twins for smart manufacturing: a case of emerging economy Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-21 Bhaskar B. Gardas, Angappa Gunasekaran, Vaibhav S. Narwane
The Industry 4.0/smart manufacturing paradigm has significantly changed the activities and processes of organizations. Emergent smart manufacturing technology called a ‘Digital Twin’ (DT) aids orga...
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Human-robot interaction for extraction of robotic disassembly information Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-21 Joao Paulo Jacomini Prioli, Jeremy L. Rickli
Disassembly of end-of-use products is critical to the economic feasibility of circular feedstock, reusing, recycling and remanufacturing loops. High-volume disassembly operations are constrained by...
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A framework to design smart manufacturing systems for Industry 5.0 based on the human-automation symbiosis Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-20 Margherita Peruzzini, Elisa Prati, Marcello Pelicciari
The concept of Industry 5.0 (I5.0) promotes the human-centricity as the core value behind the evolution of smart manufacturing systems (SMSs), based on a novel use of digital technologies in the de...
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Evaluation of the reconfigurability of manufacturing systems based on fuzzy logic taking into account the links between the characteristics of the RMS Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-19 Kombaya Touckia Jesus
Today, faced with the global COVID-19 crisis, manufacturing systems are subject to constraints caused by an uncertain and changing environment dominated by strong international competition. In this...
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A robotic 3D printer for UV-curable thermosets: dimensionality prediction using a data-driven approach Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-18 Luis Velazquez, Genevieve Palardy, Corina Barbalata
This paper presents a robotic 3D printer specifically designed for ultraviolet (UV)-curable thermosets, whose printing parameters can be selected by using a predictive modeling strategy. A speciali...
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Using machine learning for cutting tool condition monitoring and prediction during machining of tungsten Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-15 Samuel Omole, Hakan Dogan, Alexander J G Lunt, Simon Kirk, Alborz Shokrani
Machining of single-phase tungsten, used as a plasma facing material in fusion energy reactors, is commonly associated with rapid tool wear and short tool life. Conventional methods of monitoring t...
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Robust safety zones for manipulators with uncertain dynamics in collaborative robotics Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-14 Lorenzo Scalera, Carlo Nainer, Andrea Giusti, Alessandro Gasparetto
In this paper, an approach for computing online safety zones for collaborative robotics in a robust way, despite uncertain robot dynamics, is proposed. The strategy implements the speed and separat...
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Data-driven and knowledge-guided prediction model of milling tool life grade Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-18 Fuqiang Zhang, Fengli Xu, Xueliang Zhou, Kai Ding, Shujun Shao, Chao Du, Jiewu Leng
Models that predict tool life based on wear mechanism knowledge are typically inaccurate, as the use of simplified model parameters can have a significant effect on this prediction. While a tool li...
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Proposal of a maturity model for additive manufacturing: theoretical development and case study in automotive industry Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-14 Elisa Reboredo, Pedro Espadinha-Cruz
ABSTRACT Currently, organizations in the manufacturing sector are exposed to high levels of competition and constant changes in consumer requirements. To survive in an increasingly competitive environment, it is essential to adopt new technologies to ensure success in a sector that is currently going through the fourth industrial revolution, associated with Industry 4.0 (I4.0). Additive manufacturing
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The deep learning-based equipment health monitoring model adopting subject matter expert Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-15 Jr-Fong Dang
The emergence of Industry 4.0 has led to the development of modern production machines that are usually equipped with advanced sensors to collect data for further analysis. This study proposes a de...
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Production system efficiency optimization through application of a hybrid artificial intelligence solution Int. J. Comput. Integr. Manuf. (IF 4.1) Pub Date : 2023-09-14 Joao Henrique Cavalcanti, Tibor Kovacs, Andrea Ko, Károly Pocsarovszky
ABSTRACT Industry 4.0 seeks waste reduction via the optimization of production systems integrating technology and process. In addition to evaluating existing methods and technologies, academia also develops new ones. This research proposes a new hybrid artificial intelligence (AI) solution for production system efficiency optimization that combines data envelopment analysis (DEA), machine learning