Methodology for Knowledge-Based Engineering Template Update

Kuhn, Olivier; Liese, Harald; Stjepandić, Josip

doi:10.1007/978-3-642-22182-8_14

Cited by 21 publications

(11 citation statements)

References 11 publications

(12 reference statements)

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“…The number of iterations is reduced and the product emerges naturally by enriching a simplified model, driven by the material. Future work in this field might focus on adapting the Design by Material method to different expert areas, using CAD knowledge-based engineering templates (Kuhn et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Design by Material: From Material to Form Through Cad Modelling

et al. 2021

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For Aristotelian scholars, matter is identified as the subject of change, while form is the boundary of matter. Design is a process of bringing about change. From a design perspective, material is what an entity is made from; form is what makes a thing what it is. Based on the principle, “form is the boundary of matter”, this paper proposes a Design by Material method, thereby addressing the knowledge gap of a systematic method for designing according to material. This method is predicated on the material specification as the first input in the design process. A formal model is built in which the material acts as a trigger and driver for the design process. The method is implemented by integrating computer-aided design (CAD) modelling and its design form. A design application is explained to demonstrate the relevance of the Design by Material method.

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Section: Discussionmentioning

confidence: 99%

Design by Material: From Material to Form Through Cad Modelling

et al. 2021

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“…Fourthly, the process chain as such contains of several step and can be improved in term of performance and stability. Further simplification can be achieved by using intelligent templates [29] ensuring a deeper modularity [11]. Use of an alternative recognition method with multiple representations can be taken into account too [30].…”

Section: Discussionmentioning

confidence: 99%

Automated Generation of a Digital Twin of a Manufacturing System by Using Scan and Convolutional Neural Networks

Sommer¹,

Stjepandić²,

Stobrawa³

et al. 2020

Advances in Transdisciplinary Engineering

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The simulation of production processes using a Digital Twin is a promising means for prospective planning, analysis of existing systems or process-parallel monitoring. However, many companies, especially small and medium-sized enterprises, do not apply the technology, because the generation of a Digital Twin is cost-, time- and resource-intensive and IT expertise is required. This obstacle can be removed by a novel approach to generate a Digital Twin using fast scans of the shop floor and subsequent object recognition in the point cloud. We describe how parameters and data should be acquired in order to generate a Digital Twin automatically. An overview of the entire process chain is given. A particular attention is given to the automatic object recognition and its integration into Digital Twin.

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“…Complex procedures as described in previous research [8][9] usually are being controlled by appropriate workflow software. Prior of such an implementation, it must be defined how the process steps scan, object recognition and generation of Digital Twin (Figure 1) interact with each other [12]. Basically, that are tasks for different user profiles because the present technology does not provide the performance to collect entire functionality for generation of Digital Twin in one device (e. g. portable computer).…”

Section: Process Definitionmentioning

confidence: 99%

Automated Generation of a Digital Twin of a Process Plant by Using 3D Scan and Artificial Intelligence

Grau¹,

Korol²,

Lützenberger³

et al. 2021

Advances in Transdisciplinary Engineering

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The simulation of production processes using a Digital Twin is a promising tool for predictive planning, analysis of existing systems or process-parallel monitoring. In the process industry, the concept of Digital Twin provides significant support for process optimization. The generation of the Digital Twin of an already existing plant is a major challenge – in particular for small and medium-sized enterprises. In this sense, the twinning of the existing physical environment has got a particular importance due to high effort. Shape segmentation from unstructured (e.g. point cloud data) is a core step of the digital twinning process for industrial facilities. This is an inherent issue of Product Lifecycle Management how to acquire data of existing goods. The practice of Digital Twin is described based on object recognition by using methods of Machine Learning. The exploration of the pipeline semantics presents a particular challenge. The highly automated procedure for the generation of Digital Twin is described based on a use case of a biogas plant. Commercial deployment, pitfalls, drawbacks and potential for further developments are further explored.

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Methodology for Knowledge-Based Engineering Template Update

Cited by 21 publications

References 11 publications

Design by Material: From Material to Form Through Cad Modelling

Design by Material: From Material to Form Through Cad Modelling

Automated Generation of a Digital Twin of a Manufacturing System by Using Scan and Convolutional Neural Networks

Automated Generation of a Digital Twin of a Process Plant by Using 3D Scan and Artificial Intelligence

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