Knowledge Graph Supported Machine Parameterization for the Injection Moulding Industry

Bachhofner, Stefan; Kurniawan, Kabul; Kiesling, Elmar; Revoredo, Kate; Bayomie, Dina

doi:10.1007/978-3-031-21422-6_8

Cited by 3 publications

(4 citation statements)

References 14 publications

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“…By analyzing data on factors such as machine utilization, production rates, and energy consumption, a CDT can identify opportunities for optimization and provide recommendations to operators. This can lead to improved efficiency and reduced costs [21,28]. However, CDT technology is still in early stages and has limited application in modular production systems.…”

Section: Cdt Application On the Production Line Of Modular Production...mentioning

confidence: 99%

“…Once the digital model has been created, data must be collected to create the DT. These data may come from a variety of sources, including historical performance data, real-time sensor data, and information on the performance characteristics of different components [28]. The DT can then be used to simulate different scenarios and test potential changes or improvements to the system.…”

Section: Establishment Of Production Line and Cdt And Their Implement...mentioning

confidence: 99%

“…To support this level of flexibility, it is important to have a modular system architecture that allows for easy reconfiguration and adaptation. This may involve the use of standardized components and interfaces, as well as the use of flexible manufacturing cells that can be easily reconfigured to support different production requirements [28].…”

Section: Establishment Of Production Line and Cdt And Their Implement...mentioning

confidence: 99%

“…Optimizing each component improves the performance. CMP improves production efficiency and productivity by optimizing individual modules [28].…”

Section: Cognitive Modular Production (Cmp)mentioning

confidence: 99%

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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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Section: Cdt Application On the Production Line Of Modular Production...mentioning

confidence: 99%

Section: Establishment Of Production Line and Cdt And Their Implement...mentioning

confidence: 99%

Section: Establishment Of Production Line and Cdt And Their Implement...mentioning

confidence: 99%

“…Optimizing each component improves the performance. CMP improves production efficiency and productivity by optimizing individual modules [28].…”

Section: Cognitive Modular Production (Cmp)mentioning

confidence: 99%

See 2 more Smart Citations

Exploring the Fusion of Knowledge Graphs into Cognitive Modular Production

Jaryani,

Yitmen,

Sadri

et al. 2023

Buildings

View full text Add to dashboard Cite

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Examining the Adoption of Knowledge Graphs in the Manufacturing Industry: A Comprehensive Review

Martinez-Gil,

Hoch,

Pichler

et al. 2023

Artificial Intelligence in Manufacturing

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The integration of Knowledge Graphs (KGs) in the manufacturing industry can significantly enhance the efficiency and flexibility of production lines and improve product quality. By integrating and contextualizing information about devices, equipment, production resources, location, usage, and related data, KGs can be a powerful operational tool. Moreover, KGs can contribute to the intelligence of manufacturing processes by providing insights into the complex and competitive manufacturing landscape. This research work presents a comprehensive analysis of the current trends utilizing KG in the manufacturing sector. We provide an overview of the state of the art in KG applications in manufacturing and highlight the critical issues that need to be addressed to enable a successful implementation. Our research aims to contribute to advancing KG technology in manufacturing and realizing its full potential to enhance manufacturing operations and competitiveness.

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