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Internet of Production: Fundamentals, Applications and ProceedingsНазвание: Internet of Production: Fundamentals, Applications and Proceedings
Автор: Christian Brecher, Gunther Schuh, Wil van der Aalst, Matthias Jarke
Издательство: Springer
Год: 2023
Страниц: 153
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Changes in society require changes in our industrial production. In order to remain competitive in the future, the masses of data available in production must be used urgently. This is still a challenge because data are often not accessible or understandable. Therefore, we developed the Internet of Production (IoP) concept which aims to collect, unify, and exploit different data sources and improve production. To this end, the various research domains of production technology, the need for a common infrastructure, and the concept of the Digital Shadow are presented. The vision can only be achieved through interdisciplinary cooperation between different disciplines. Therefore, the joint approach is explained and common research topics are presented. Interdisciplinary cooperation is the key for further steps to achieve the common vision.

The internet and approaches such as the Internet of Things (IoT) have revolutionized the availability of data and knowledge. Therefore, advances under the terms such as Industry 4.0, the Industrial Internet of Things (IIoT), and Made in China 2025 have been made to combine technological advances in Internet and Communication Technologies with the production technology. However, these concepts cannot be transferred holistically to production technology. The number of parameters in production plays a decisive role here. So for knowledge to be generated from data in the production context, these data sources need to be extremely networked, contextualized, aggregated, and processed. An Internet of Production is necessary.

The following vision was defined for this:
The vision of the Internet of Production (IoP) is to enable a new level of cross-domain collaboration by providing semantically adequate and context-aware data from production, development and usage in real-time, on an adequate level of granularity.

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