Keine Industrie 4.0 ohne den Digitalen Schatten

Schuh, Günther; Walendzik, Pia; Luckert, Melanie; Birkmeier, Martin; Weber, Anja; Blum, Matthias

doi:10.3139/104.111613

Cited by 17 publications

(3 citation statements)

References 8 publications

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“…The potential of fully automated workflows or even fully automated laboratories in academic bioprocess development laboratories is yet to be discovered and will also not be possible everywhere due to the need of high flexibility and complexity. Dividing whole processes into sub‐processes, developing a digital twin (Subsection 2.3 ), using a modular setup, and staying flexible throughout the planning will help to automate a whole workflow ultimately [ 7 , 8 , 28 , 74 , 75 ].…”

Section: Digitalization Strategiesmentioning

confidence: 99%

Digitalization concepts in academic bioprocess development

Habich,

Beutel

2024

Engineering in Life Sciences

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Digitalization with integrated devices, digital and physical assistants, automation, and simulation is setting a new direction for laboratory work. Even with complex research workflows, high staff turnover, and a limited budget some laboratories have already shown that digitalization is indeed possible. However, academic bioprocess laboratories often struggle to follow the trend of digitalization. Due to their diverse research circumstances, high variety of team composition, goals, and limitations the concepts are substantially different. Here, we will provide an overview on different aspects of digitalization and describe how academic laboratories successfully digitalized their working environment. The key aspect is the collaboration and communication between IT‐experts and scientific staff. The developed digital infrastructure is only useful if it supports the laboratory worker and does not complicate their work. Thereby, laboratory researchers have to collaborate closely with IT‐experts in order for a well‐developed and maintainable digitalization concept that fits their individual needs and level of complexity. This review may serve as a starting point or a collection of ideas for the transformation toward a digitalized laboratory.

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Section: Digitalization Strategiesmentioning

confidence: 99%

Digitalization concepts in academic bioprocess development

Habich,

Beutel

2024

Engineering in Life Sciences

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“…The data can originate from different data sources and do not have to be homogeneous, structured or centrally available. The DS thus serves to filter, link, abstract and aggregate the data with reference to the specific problem [31]. The digital twin (DT), in turn, relies on the DS by automating the data flow bidirectionally.…”

Section: Digital Shadowmentioning

confidence: 99%

Design Model for the Digital Shadow of a Value Stream

Frick,

Terwolbeck,

Seibel

et al. 2024

Systems

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The value stream method, a key tool in industry to analyze and visualize value streams in production, aims to holistically optimize process steps, reduce waste, and achieve continuous material flow. However, this method primarily relies on data from a single on-site inspection, which is subjective and represents just a snapshot of the process. This limitation can lead to uncertainty and potentially incorrect decisions, especially in industries producing customer-specific products. The increasing digitization in production offers a solution to this limitation by supporting the method through data provision. The concept of the digital shadow emerges as a key tool that systematically captures, processes, and integrates necessary data into a model to enhance traditional value stream mapping. This addresses the method’s shortcomings, especially in heterogeneous IT landscapes and complex value streams. To effectively implement the digital shadow this study identifies concepts of digital shadows and their key components and evaluates them for their relevance in industrial environments using an expert study. Based on the results, a design model is defined. This model entails guidelines to support companies with the practical implementation of the digital shadow of a value stream. Lastly, the model is evaluated on a realistic value stream in a learning factory.

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“…With this knowledge, data-driven modelling of cause-andeffect relationships in fine blanking and thus novel ways of product and process design can be enabled. Additionally, digital twins enable greater transparency in production and individual optimization of products along the entire value chain [6].…”

Section: Introductionmentioning

confidence: 99%

Development of a hybrid DLT cloud architecture for the automated use of finite element simulation as a service for fine blanking

Stanke

Unterberg

Trauth

et al. 2020

Int J Adv Manuf Technol

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Networking and digitization in manufacturing enable novel methods of data-driven analysis and optimization of processes through cross-process data availability. The creation of digital twins plays an important role in this. However, not all data relevant for a digital twin can be measured directly in the process. Therefore, methods are needed that enable the modelling of quantities that are difficult or impossible to measure directly in the process, such as the finite element method. In many companies, however, neither the know-how nor the necessary IT infrastructure for finite element simulations is available. External commissioning processes are also not suitable for achieving the goals of higher productivity and agility pursued with the digitization and networking of manufacturing processes. In this contribution, an architecture is presented that enables the fully automated use of finite element simulation as a service. The architecture is developed using the case study of fine blanking. First, the requirements of the architecture to be created are determined. Important characteristics of the architecture should be scalability as well as interfaces and means of payment suitable for machine communication. In addition, ensuring data integrity is an important requirement when creating the digital twin. Based on the identified requirements, an architecture is then presented that meets these requirements by using cloud computing and distributed ledger technologies and interfaces that can directly process measurement signals from the process and communicate with the architecture. Finally, the capability of the architecture is tested, possible applications and limitations are discussed, and future extensions are considered.

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Keine Industrie 4.0 ohne den Digitalen Schatten

Cited by 17 publications

References 8 publications

Digitalization concepts in academic bioprocess development

Digitalization concepts in academic bioprocess development

Design Model for the Digital Shadow of a Value Stream

Development of a hybrid DLT cloud architecture for the automated use of finite element simulation as a service for fine blanking

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