Internet of Things (IoT) is an emerging domain that promises ubiquitous connection to the Internet, turning common objects into connected devices. The IoT paradigm is changing the way people interact with things around them. It paves the way for creating pervasively connected infrastructures to support innovative services and promises better flexibility and efficiency. Such advantages are attractive not only for consumer applications, but also for the industrial domain. Over the last few years, we have been witnessing the IoT paradigm making its way into the industry marketplace with purposely designed solutions. In this paper, we clarify the concepts of IoT, Industrial IoT, and Industry 4.0. We highlight the opportunities brought in by this paradigm shift as well as the challenges for its realization. In particular, we focus on the challenges associated with the need of energy efficiency, real-time performance, coexistence, interoperability, and security and privacy. We also provide a systematic overview of the state-of-the-art research efforts and potential research directions to solve Industrial IoT challenges.

Industrial Internet of Things: Challenges, Opportunities, and Directions

With the introduction of the Internet of Things (IoT) and cyberphysical system (CPS) concepts in industrial application scenarios, industrial automation is undergoing a tremendous change. This is made possible in part by recent advances in technology that allow interconnection on a wider and more fine-grained scale. The purpose of this article is to review technological trends and the impact they may have on industrial communication. We will review the impact of IoT and CPSs on industrial automation from an industry 4.0 perspective, give a survey of the current state of work on Ethernet time-sensitive networking (TSN), and shed light on the role of fifth-generation (5G) telecom networks in automation. Moreover, we will point out the need for harmonization beyond networking.

The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0

One of the most significant advances in the development of computer science, information and communication technologies is represented by the cyber-physical systems (CPS). They are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the Internet. Cyber-physical production systems (CPPS), relying on the latest, and the foreseeable further developments of computer science, information and communication technologies on one hand, and of manufacturing science and technology, on the other, may lead to the 4th industrial revolution, frequently noted as Industrie 4.0. The paper underlines that there are significant roots in general – and in particular to the CIRP community – which point towards CPPS. Expectations towards research in and implementation of CPS and CPPS are outlined and some case studies are introduced. Related new R&D challenges are highlighted.

Cyber-physical systems in manufacturing

This paper provides an overview of the recent developments in data-based techniques focused on modern industrial applications. As one of the hottest research topics for complicated processes, the data-based techniques have been rapidly developed over the past two decades and widely used in numerous industrial sectors nowadays. The core of data-based techniques is to take full advantage of the huge amounts of available process data, aiming to acquire the useful information within. Compared with the well-developed model-based approaches, data-based techniques provide efficient alternative solutions for different industrial issues under various operating conditions. The main objective of this paper is to review and summarize the recent achievements in data-based techniques, especially for complicated industrial applications, thus providing a referee for further study on the related topics both from academic and practical points of view. This paper begins with a brief evolutionary overview of data-based techniques in the last two decades. Then, the methodologies only based on process measurements and the model-data integrated techniques will be further introduced. The recent developments for modern industrial applications are, respectively, presented mainly from perspectives of monitoring and control. The new trends of data-based technique as well as potential application fields are finally discussed.

Data-Based Techniques Focused on Modern Industry: An Overview

In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systems for wireless industrial communications. We have selected topics that have either emerged as hot topics in the industrial communications community in the last few years (like wireless sensor networks), or which could be worthwhile research topics in the next few years (for example cooperative diversity techniques for error control, cognitive radio/opportunistic spectrum access for mitigation of external interferences).

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Recent and Emerging Topics in Wireless Industrial Communications: A Selection

Die ganzheitliche Digitalisierung wirkt sich auch auf die Prozesse in der industriellen Produktionslandschaft aus. Die derzeitigen heterogenen Architekturen, bestehend aus drahtgebundenen und drahtlosen Technologien bzw. Protokollen, bringen neue Anforderungen an ein zukunftssicheres Netzwerkmanagement. Daher werden neue Ansatze zur Sicherstellung und Uberwachung von Quality of Service (QoS) Parametern benotigt. Das eng damit verbundene Thema der Informationssicherheit ist in der Vergangenheit allerdings weitgehend ignoriert worden. Dennoch steigen die Aufmerksamkeit und das Interesse daran, da es vermehrt Berichte uber sicherheitsrelevante Vorfalle, wie Industriespionage oder die gezielte Manipulation von industriellen Produktionssystemen, gibt. In diesem Bereich sind bereits verschiedene Standards und Richtlinien zur Absicherung industrieller Anlagen verfugbar, die jedoch hauptsachlich zyklisch, statisch und manuell durchgefuhrt werden mussen. Die vorgeschlagene Losung bietet einen dynamischen, maschinenlesbaren, automatischen und zukunftssicheren Ansatz zur Modellierung und Verarbeitung von Anforderungen bezuglich der Informationssicherheit fur das industrielle Netzwerkmanagement.

Automatische Evaluierung von Anforderungen bezüglich der Informationssicherheit für das zukünftige industrielle Netzwerkmanagement

Das neue Geschäftsmodell, das mit der Industrie 4.0 verbunden ist, verändert ein etabliertes Dogma der Automatisierungsbranche: Anlagen wurden auf hohen Durchsatz der immer gleichen Produktformate optimiert. Während derartige Systeme mit bekannten Maßnahmen automatisierbar sind, stellt die Variantenfertigung eher ein Automatisierungshindernis dar. Für eine individualisierte Produktion ist die Rekonfigurierbarkeit von Industrieanlagen ein wichtiger Faktor. Die Modularisierung und automatische Konfiguration sind hierbei wesentliche Triebkräfte. Im Rahmen dieser Arbeit wird eine Basisarchitektur für eine intelligente Netzwerkkomponente vorgestellt, die ohne manuelle Konfiguration in unterschiedlichen Echtzeit-Ethernet-Netzwerken eingesetzt werden kann.

Universelle Echtzeit-Ethernet Architektur zur Integration in rekonfigurierbare Automatisierungssysteme

Abstract Manufacturing systems based on Industry 4.0 concepts provide a greater availability of data and have modular characteristics enabling frequent changes. This raises the need for new security engineering concepts that cover the increasing complexity and frequency of mandatory security risk assessments. In contrast, the current standardization landscape used for the assessment of these systems only offers abstract, static, manual, and resource-intensive procedures. Therefore, this work proposes a method that further specifies the IEC 62443 aiming to automate the security risk assessments in such a way that manual efforts can be reduced and a consistent quality can be achieved. The methodology is presented using network segmentation as a guiding example and consists of four main steps: Information collection based on a process analysis, information formalisation with a semi-formal model, information usage applying first order logic to extract expert knowledge, and information access using the concept of the digital twin. In addition, the applicability of the IEC 62443 standard to the risk assessment of modular manufacturing systems is evaluated.

Towards automated risk assessments for modular manufacturing systems

Real-Time Communication in Industrial Automation with Switched Ethernet Networks

Sub-optimal control policies in intersection traffic signal controllers (TSC) contribute to congestion and lead to negative effects on human health and the environment. Reinforcement learning (RL) for traffic signal control is a promising approach to design better control policies and has attracted considerable research interest in recent years. However, most work done in this area used simplified simulation environments of traffic scenarios to train RL-based TSC. To deploy RL in real-world traffic systems, the gap between simplified simulation environments and real-world applications has to be closed. Therefore, we propose LemgoRL, a benchmark tool to train RL agents as TSC in a realistic simulation environment of Lemgo, a medium-sized town in Germany. In addition to the realistic simulation model, LemgoRL encompasses a traffic signal logic unit that ensures compliance with all regulatory and safety requirements. LemgoRL offers the same interface as the well-known OpenAI gym toolkit to enable easy deployment in existing research work. Our benchmark tool drives the development of RL algorithms towards real-world applications. We provide LemgoRL as an open-source tool at this https URL.

Jurgen Jasperneite

Papers

Automatische Evaluierung von Anforderungen bezüglich der Informationssicherheit für das zukünftige industrielle Netzwerkmanagement

Universelle Echtzeit-Ethernet Architektur zur Integration in rekonfigurierbare Automatisierungssysteme

Towards automated risk assessments for modular manufacturing systems

Real-Time Communication in Industrial Automation with Switched Ethernet Networks

LemgoRL: An open-source Benchmark Tool to Train Reinforcement Learning Agents for Traffic Signal Control in a real-world simulation scenario.