A six-layer architecture for the digital twin: a manufacturing case study implementation

Redelinghuys, A. J. H.; Basson, Anton; Kruger, Karel

doi:10.1007/s10845-019-01516-6

Cited by 188 publications

(87 citation statements)

References 19 publications

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“…Therefore, each data collection signal time impulse had to be modified to ensure correct data collection. A similar problem with latencies was reported by Redelinghuys et al [27].…”

Section: Discussionsupporting

confidence: 81%

Implementation of Digital Twin for Engine Block Manufacturing Processes

et al. 2020

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The digital twin (DT) is undergoing an increase in interest from both an academic and industrial perspective. Although many authors proposed and described various frameworks for DT implementation in the manufacturing industry context, there is an absence of real-life implementation studies reported in the available literature. The main aim of this paper is to demonstrate feasibility of the DT implementation under real conditions of a production plant that is specializing in manufacturing of the aluminum components for the automotive industry. The implementation framework of the DT for engine block manufacturing processes consists of three layers: physical layer, virtual layer and information-processing layer. A simulation model was created using the Tecnomatix Plant Simulation (TPS) software. In order to obtain real-time status data of the production line, programmable logic control (PLC) sensors were used for raw data acquisition. To increase production line productivity, the algorithm for bottlenecks detection was developed and implemented into the DT. Despite the fact that the implementation process is still under development and only partial results are presented in this paper, the DT seems to be a prospective real-time optimization tool for the industrial partner.

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“…Therefore, each data collection signal time impulse had to be modified to ensure correct data collection. A similar problem with latencies was reported by Redelinghuys et al [27].…”

Section: Discussionsupporting

confidence: 81%

Implementation of Digital Twin for Engine Block Manufacturing Processes

et al. 2020

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“…Horizontal and vertical integration can be supported by digital twin solutions. A publication reported the application of a digital twin, which provides service-based and real-time enabled infrastructure for vertical and horizontal integration [32]. Another paper introduced a viewpoint-oriented approach to identify functional components that facilitate decision-making within a manufacturing ecosystem [33].…”

Section: Levelmentioning

confidence: 99%

Industry 4.0‐Driven Development of Optimization Algorithms: A Systematic Overview

et al. 2021

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The Fourth Industrial Revolution means the digital transformation of production systems. Cyber-physical systems allow for the horizontal and vertical integration of these production systems as well as the exploitation of the benefits via optimization tools. This article reviews the impact of Industry 4.0 solutions concerning optimization tasks and optimization algorithms, in addition to the identification of the new R&D directions driven by new application options. The basic organizing principle of this overview of the literature is to explore the requirements of optimization tasks, which are needed to perform horizontal and vertical integration. This systematic review presents content from 900 articles on Industry 4.0 and optimization as well as 388 articles on Industry 4.0 and scheduling. It is our hope that this work can serve as a starting point for researchers and developers in the field.

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“…The virtual models could understand the state of the physical entities through sensing data, to predict, estimate, and analyse the dynamic changes. While the physical objects would respond to the changes according to the optimized scheme from simulation (Redelinghuys et al 2020;Tong et al 2020;Mukherjee and DebRoy 2019).…”

Section: Digital Twin: a New Concept Of Gating System Design In 3d Printed Molds For Sand Castingmentioning

confidence: 99%

Digital twin of functional gating system in 3D printed molds for sand casting using a neural network

Ktari

Mansori

2020

J Intell Manuf

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The filling stage is a critical phenomenon in sand casting for making reliable castings. Latest research has demonstrated that for most liquid engineering alloys, the critical meniscus velocity of the melt at the ingate is in the range of 0.4-0.6 m s −1 . The work described in this research paper is to use neural network (NN) technology to propose digital twin approach for gating system design that allow to understand and model its performances faster and more reliable than traditional methods. This approach was applied in the case of sand casting of liquid aluminum alloy (EN AC-44200). The approach is based first on a digital representation of filling process to perform the melt flow simulations using a combination of the gating system design parameters, selected as a training cases from Taguchi orthogonal array (OA). The second step of the approach is the data capture of functional gating design system to train up the feed-forward back-propagation NN model. The validation of the well-trained NN model is assessed by interrogating predicted ingate velocity to it and making reliable predictions with high accuracy. The claim is that such digital twin approach is an effective solution to recognize the functional design parameters from the entire filling systems used during casting process.

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A six-layer architecture for the digital twin: a manufacturing case study implementation

Cited by 188 publications

References 19 publications

Implementation of Digital Twin for Engine Block Manufacturing Processes

Implementation of Digital Twin for Engine Block Manufacturing Processes

Industry 4.0‐Driven Development of Optimization Algorithms: A Systematic Overview

Digital twin of functional gating system in 3D printed molds for sand casting using a neural network

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