Challenges of the digital transformation: The role of sensors, sensor networks, IoT-devices, and 5G : Invited Paper

Ahrend, Ulf; Aleksy, Markus; Berning, Matthias; Gebhardt, Jörg; Mendoza, Francisco; Schulz, Dirk

doi:10.1109/sa47457.2019.8938077

Cited by 8 publications

(7 citation statements)

References 12 publications

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“…Nevertheless, taking process industries as an example, it is well-known that pervasive sensing cannot be accomplished with measurement instruments as they have been used before [ 30 ]. In today’s process plants, high-quality instrumentation is the basis of the automation system and sophisticated process control loops.…”

Section: Key Aspects Of Industrial Cpsmentioning

confidence: 99%

“…From the extensive list of new required sensor features as described in [ 30 ], we underline a few features, which are illustrated by the use cases in Section 3 and are relevant for the success of CPS.…”

Section: Key Aspects Of Industrial Cpsmentioning

confidence: 99%

“…In summary, the first measurable benefit of the new type of sensors—and also of many types of CPS—will probably be seen in M+O. A possible next step, for instrumentation suppliers as well as for users, is to move a considerable number of CPS applications from traditional instrumentation to new sensor paradigms [ 30 ] under the framework of a CPS. The developments in sensor technology and industrial applications lay the foundation for the development in the level of maturity of Industrie 4.0 as they are discussed in Section 5.8 .…”

Section: Key Aspects Of Industrial Cpsmentioning

confidence: 99%

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Developing Industrial CPS: A Multi-Disciplinary Challenge

Hoffmann¹,

Malakuti²,

Grüner³

et al. 2021

Sensors

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Industrial Cyber–Physical System (CPS) is an emerging approach towards value creation in modern industrial production. The development and implementation of industrial CPS in real-life production are rewarding yet challenging. This paper aims to present a concept to develop, commercialize, operate, and maintain industrial CPS which can motivate the advance of the research and the industrial practice of industrial CPS in the future. We start with defining our understanding of an industrial CPS, specifying the components and key technological aspects of the industrial CPS, as well as explaining the alignment with existing work such as Industrie 4.0 concepts, followed by several use cases of industrial CPS in practice. The roles of each component and key technological aspect are described and the differences between traditional industrial systems and industrial CPS are elaborated. The multidisciplinary nature of industrial CPS leads to challenges when developing such systems, and we present a detailed description of several major sub-challenges that are key to the long-term sustainability of industrial CPS design. Since the research of industrial CPS is still emerging, we also discuss existing approaches and novel solutions to overcome these sub-challenges. These insights will help researchers and industrial practitioners to develop and commercialize industrial CPS.

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Section: Key Aspects Of Industrial Cpsmentioning

confidence: 99%

Section: Key Aspects Of Industrial Cpsmentioning

confidence: 99%

Section: Key Aspects Of Industrial Cpsmentioning

confidence: 99%

See 1 more Smart Citation

Developing Industrial CPS: A Multi-Disciplinary Challenge

Hoffmann¹,

Malakuti²,

Grüner³

et al. 2021

Sensors

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“…The development of communication and sensor technology was strongly driven by the consumer electronics industry during the last decade. These technologies nowadays enter industrial applications and enable them to equip machinery with sensor networks [117]. The first examples of such sensor systems for usage in electrical installations have been demonstrated recently [118] and promise to pave the way to a digitalization of the electricity network.…”

Section: Distribution Grid Assets and Monitoringmentioning

confidence: 99%

Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

Hoffmann¹,

Wildermuth²,

Gitzel³

et al. 2020

Sensors

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The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.

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“…Digitalization and Industry 4.0 have created a new industrial environment for sensors [1]. Flexible measurement solutions for monitoring and optimization that can be cost effectively and reliably installed in existing plants are key sources of new insights into industrial processes [2].…”

Section: Introduction -The Relevance Of Non-invasive Temperature Measmentioning

confidence: 99%

Non-invasive temperature measurement of turbulent flows of aqueous solutions and gases in pipes

Gebhardt

Sosale²,

Dasgupta

2020

Tm - Technisches Messen

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Accurate and responsive non-invasive temperature measurements are enablers for process monitoring and plant optimization use cases in the context of Industry 4.0. If their performance is proven for large classes of applications, such measurement principles can replace traditional invasive measurements. In this paper we describe a two-step model to estimate the process temperature from a pipe surface temperature measurement. This static case model is compared to and enhanced by computational fluid dynamic (CFD) calculations to predict transient situations. The predictions of the approach are validated by means of controlled experiments in a laboratory environment. The experimental results demonstrate the efficacy of the model, the responsiveness of the pipe surface temperature, and that state of the art industrial non-invasive sensors can achieve the performance of invasive thermowells. The non-invasive sensors are then used to demonstrate the performance of the model in industrial applications for cooling fluids and steam.

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Challenges of the digital transformation: The role of sensors, sensor networks, IoT-devices, and 5G : Invited Paper

Cited by 8 publications

References 12 publications

Developing Industrial CPS: A Multi-Disciplinary Challenge

Developing Industrial CPS: A Multi-Disciplinary Challenge

Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

Non-invasive temperature measurement of turbulent flows of aqueous solutions and gases in pipes

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