Real-time combination of material flow simulation, digital twins of manufacturing cells, an AGV and a mixed-reality application

Müller, Marcel; Mielke, Jonas; Pavlovskyi, Yurii; Pape, Andreas; Masik, Steffen; Reggelin, Tobias; Häberer, Sebastian

doi:10.1016/j.procir.2021.11.271

Cited by 14 publications

(4 citation statements)

References 7 publications

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“…CPS-based processing of data directly on the object, e.g., the machine, allows for faster response times in the case of unforeseen events (Section 2.1). Furthermore, the resulting information can be transferred into a DT and made available to the responsible persons and systems (Freier & Schumann, 2020;Müller et al, 2021). However, this usually only happens on a low hierarchical level, e.g., machines, of the industrial production environment.…”

Section: Problem Identificationmentioning

confidence: 99%

“…In the context of an industrial production environment, especially concerning digitization and modernization (Industry 4.0), DTs can map machines including their CPS and the volume of generated information. DTs of machines are also able, for example, to simulate the manufacturing behavior of a machine for different products (Müller et al, 2021). Although DTs are not a new concept, previous research on this topic falls short given the high product complexity and manufacturing processes involving a large number of production sites or machines (Jiang et al, 2021;Kong et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Human-AI Interaction – Is It Trust or Emotions That Mediates Behavioral Intensions?

Yao,

Holopainen,

Laukkanen

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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The increasing requirements for industrial production environments due to customer expectations, the implementation of batch size 1, and further automation of production processes are confronting companies with new challenges. In particular, the emergence of cyber-physical systems is influencing and complicating manufacturing processes by capturing an increasing amount of information within production facilities. Digital twins are an interdisciplinary technology that may solve these issues because they serve to monitor, control, and optimize cyber-physical systems by creating a digital representation of realworld objects. Existing concepts for digital twins usually only consider individual machines without their context. This is of limited use for production environments due to a multitude of different machines and associated sensor types. Therefore, we propose a requirements catalog, concept, and prototypical implementation for the hierarchical structuring of digital twins in this paper.

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Section: Problem Identificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Human-AI Interaction – Is It Trust or Emotions That Mediates Behavioral Intensions?

Yao,

Holopainen,

Laukkanen

2024

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Using AR and DT in CNC machining operations for visualization and communication (voice/gesture commands) [66] COMSOL Multiphysics DT of an Optical Fiber Drawing Process is used for real-time monitoring and evaluation (using DL algorithms) of process parameters and quality control [129] Siemens Tecnomatix Process planning and configuration for manufacturing of an impeller using industrial robots, machine tools, and an AGV in a with a DT based Cyber-Physical Production System (CPPS) [130] VINCENT Unity…”

Section: Ref Year Toolsmentioning

confidence: 99%

Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies

Asad

Khan

Khalid

et al. 2023

Sensors

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The last decade saw the emergence of highly autonomous, flexible, re-configurable Cyber-Physical Systems. Research in this domain has been enhanced by the use of high-fidelity simulations, including Digital Twins, which are virtual representations connected to real assets. Digital Twins have been used for process supervision, prediction, or interaction with physical assets. Interaction with Digital Twins is enhanced by Virtual Reality and Augmented Reality, and Industry 5.0-focused research is evolving with the involvement of the human aspect in Digital Twins. This paper aims to review recent research on Human-Centric Digital Twins (HCDTs) and their enabling technologies. A systematic literature review is performed using the VOSviewer keyword mapping technique. Current technologies such as motion sensors, biological sensors, computational intelligence, simulation, and visualization tools are studied for the development of HCDTs in promising application areas. Domain-specific frameworks and guidelines are formed for different HCDT applications that highlight the workflow and desired outcomes, such as the training of AI models, the optimization of ergonomics, the security policy, task allocation, etc. A guideline and comparative analysis for the effective development of HCDTs are created based on the criteria of Machine Learning requirements, sensors, interfaces, and Human Digital Twin inputs.

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“…Since the digital twin can reflect the dynamic mapping of physical products and their digital counterparts, it is considered the next wave of modeling, simulation, and optimization technologies [2]. Since the concept of the digital twin was introduced, it has been applied to many industrial fields, such as intelligent robots [3,4], AGV carts [5],…”

Section: Introductionmentioning

confidence: 99%

Fusion method for digital twin model of a production line

Liu,

Wang,

Huang

et al. 2024

Int J Adv Manuf Technol

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Digital twins have attracted more and more attention in the past few years. To put digital twins into practice, a large number of modeling approaches have been proposed, vast amounts of data have been collected, and their accuracy has been improving. However, current research has paid insufficient attention to the multi-scale features of the shop floor, which hinders the effective application of the digital twin shop floor. To address the problem of how to achieve effective multilevel and multi-dimensional fusion of digital twin models with production process data, this paper first proposes a structured data modeling framework for sorting out all the production process data collected in real-time; and then proposes a multi-level fusion framework for supporting the fusion of real-time data and twin models from the unit level to the system level. The method judges the parsed received data streams through the full-factor semanticization framework, and at the same time fuses the parsed data streams with the constructed full-factor twin model from multiple dimensions and layers, forming a twin model fusion method with real-time data streams as the blood and twin model as the skeleton. Finally, the micro-assembly-based production shop environment is selected as a case study to verify the correctness and feasibility of the proposed data grooming framework, data, and model fusion method.

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Real-time combination of material flow simulation, digital twins of manufacturing cells, an AGV and a mixed-reality application

Cited by 14 publications

References 7 publications

Human-AI Interaction – Is It Trust or Emotions That Mediates Behavioral Intensions?

Human-AI Interaction – Is It Trust or Emotions That Mediates Behavioral Intensions?

Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies

Fusion method for digital twin model of a production line

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