Towards Flexible and Cognitive Production—Addressing the Production Challenges

Hadi, Muaaz Abdul; Kraus, Daniel; Kajmaković, Amer; Suschnigg, Josef; Guiza, Ouijdane; Gashi, Milot; Sopidis, Georgios; Vuković, Matej; Milenkovic, Katarina; Haslgruebler, Michael; Brillinger, Markus; Diwold, Konrad

doi:10.3390/app12178696

Cited by 6 publications

(3 citation statements)

References 108 publications

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“…The following concepts used in this work satisfy the requirements of Industry 4.0 and challenge Industry 5.0 [ 23 , 24 , 25 , 26 , 27 ]: Digital twin with augmented reality (AR) component represents the integration of the virtual and real environments, where objects in the real world are enhanced by computer-generated information or objects that help the multi-functional flexible assembly technology. Thus, SHPN was used for technology modeling in which A/D/RML has a discrete dynamic and MCPS a continuous one; The “Digital twin” concept enables optimizing the production line and predictive maintenance that can improve efficiency and detect problems in time.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, the paper claims several concepts specific to Industry 4.0, such as: “Digital twin” of real-world application, MCPSs, IoT, cloud storage to efficiently increase autonomy, big data collection and manipulation, smart manufacturing, efficient production lines and smart products, communication security, and cybersecurity [ 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

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Digital Twin for a Multifunctional Technology of Flexible Assembly on a Mechatronics Line with Integrated Robotic Systems and Mobile Visual Sensor—Challenges towards Industry 5.0

Minca

Cernega

Șolea

et al. 2022

Sensors

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A digital twin for a multifunctional technology for flexible manufacturing on an assembly, disassembly, and repair mechatronics line (A/D/RML), assisted by a complex autonomous system (CAS), is presented in the paper. The hardware architecture consists of the A/D/RML and a six-workstation (WS) mechatronics line (ML) connected to a flexible cell (FC) and equipped with a six-degree of freedom (DOF) industrial robotic manipulator (IRM). The CAS has in its structure two driving wheels and one free wheel (2DW/1FW)-wheeled mobile robot (WMR) equipped with a 7-DOF robotic manipulator (RM). On the end effector of the RM, a mobile visual servoing system (eye-in-hand MVSS) is mounted. The multifunctionality is provided by the three actions, assembly, disassembly, and repair, while the flexibility is due to the assembly of different products. After disassembly or repair, CAS picks up the disassembled components and transports them to the appropriate storage depots for reuse. Disassembling or repairing starts after assembling, and the final assembled product fails the quality test. The virtual world that serves as the digital counterpart consists of tasks assignment, planning and synchronization of A/D/RML with integrated robotic systems, IRM, and CAS. Additionally, the virtual world includes hybrid modeling with synchronized hybrid Petri nets (SHPN), simulation of the SHPN models, modeling of the MVSS, and simulation of the trajectory-tracking sliding-mode control (TTSMC) of the CAS. The real world, as counterpart of the digital twin, consists of communication, synchronization, and control of A/D/RML and CAS. In addition, the real world includes control of the MVSS, the inverse kinematic control (IKC) of the RM and graphic user interface (GUI) for monitoring and real-time control of the whole system. The “Digital twin” approach has been designed to meet all the requirements and attributes of Industry 4.0 and beyond towards Industry 5.0, the target being a closer collaboration between the human operator and the production line.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital Twin for a Multifunctional Technology of Flexible Assembly on a Mechatronics Line with Integrated Robotic Systems and Mobile Visual Sensor—Challenges towards Industry 5.0

Minca

Cernega

Șolea

et al. 2022

Sensors

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“…Furthermore, modular production systems often lack standardization, which can make it difficult to integrate cognitive processes in a standardized and consistent manner. Another obstacle to integrating cognition into modular production systems is the need for specialized knowledge and expertise in both cognitive science and modular production systems [22,23].…”

Section: Cognition In Modular Productionmentioning

confidence: 99%

Exploring the Fusion of Knowledge Graphs into Cognitive Modular Production

Jaryani,

Yitmen,

Sadri

et al. 2023

Buildings

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Modular production has been recognized as a pivotal approach for enhancing productivity and cost reduction within the industrialized building industry. In the pursuit of further optimization of production processes, the concept of cognitive modular production (CMP) has been proposed, aiming to integrate digital twins (DTs), artificial intelligence (AI), and Internet of Things (IoT) technologies into modular production systems. This fusion would imbue these systems with perception and decision-making capabilities, enabling autonomous operations. However, the efficacy of this approach critically hinges upon the ability to comprehend the production process and its variations, as well as the utilization of IoT and cognitive functionalities. Knowledge graphs (KGs) represent a type of graph database that organizes data into interconnected nodes (entities) and edges (relationships), thereby providing a visual and intuitive representation of intricate systems. This study seeks to investigate the potential fusion of KGs into CMP to bolster decision-making processes on the production line. Empirical data were collected through a computerized self-administered questionnaire (CSAQ) survey, with a specific emphasis on exploring the potential benefits of incorporating KGs into CMP. The quantitative analysis findings underscore the effectiveness of integrating KGs into CMP, particularly through the utilization of visual representations that depict the relationships between diverse components and subprocesses within a virtual environment. This fusion facilitates the real-time monitoring and control of the physical production process. By harnessing the power of KGs, CMP can attain a comprehensive understanding of the manufacturing process, thereby supporting interoperability and decision-making capabilities within modular production systems in the industrialized building industry.

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