Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

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

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

A review of Internet of Things (IoT) embedded sustainable supply chain for industry 4.0 requirements

Cloud computing has recently emerged as a new computing paradigm in many application areas comprising office and enterprise systems. It offers various solutions to provide a dynamic and flexible infrastructure to host computing resources and deliver them as a service on-demand. Since industrial automation systems of the future have to be adaptable and agile, cloud computing can be considered as a promising solution for this area. However, the requirements of industrial automation systems differ significantly from the office and enterprise world. In this paper we describe a case study that implements a concept of PLC as a service within a cloud based infrastructure and provides a performance evaluation with respect to legacy PLCs.

Control-as-a-service from the cloud: A case study for using virtualized PLCs

Just like Ethernet before, IEEE 802.11 is now transcending the borders of its usage from the office environment toward real-time communication on the factory floor. However, similar to Ethernet, the availability of synchronized clocks to coordinate and control communication and distributed real-time services is not a built-in feature in WLAN. Over the years, this has led to the design and use of a wide variety of customized protocols with varying complexity and precision, both for wired and wireless networks, in accordance with the increasingly demanding requirements from real-time applications. This survey looks into the details of synchronization over IEEE 802.11 with a particular focus on the infrastructure mode which is most relevant for industrial use cases. It highlights the different parameters which affect the performance of clock synchronization over WLAN and compares the performance of existing synchronization methods to analyze their shortcomings. Finally, it identifies new trends and directions for future research as well as features for wireless clock synchronization which will be required by the applications in the near future.

Clock Synchronization Over IEEE 802.11—A Survey of Methodologies and Protocols

Cloud computing has recently emerged as a new computing paradigm in many application areas comprising office and enterprise systems. It offers various solutions to provide a dynamic and flexible infrastructure to host computing resources and deliver them as a service on-demand. Since industrial automation systems of the future have to be adaptable and agile, cloud computing can be considered as a promising solution for this area. However, the requirements of industrial automation systems differ significantly from the office and enterprise world. This paper provides an overview of the latest concepts of cloud computing technology for industrial automation. Existing works are categorized based on the levels of automation systems and research gaps are discussed based on these findings. A general cloud model for automation is derived from existing proposals by refining them further. This cloud model will offer automation functions as services from a dynamic infrastructure.

Cloud computing for industrial automation systems — A comprehensive overview

The exhaustive digitalization of the economy, and to be more specific, of industrial production systems results in a new quality of information transparency. This is the basis for added values in terms of effectiveness, quality, and individuality. However, these added values also result in an increased exposure to Cyber-Security threats, due to the increased digitalization, information transparency and standardization. In this work, the procedural model for a Cyber-Security analysis based on reference architecture model Industry 4.0 (RAMI 4.0) and the VDI/VDE guideline 2182 is exemplary shown for the use case of a Cloud-based monitoring of the production. The derived procedure supports the identification of protection demands and allows a risk-based selection of suitable countermeasures.

Analysis of the Cyber-Security of industry 4.0 technologies based on RAMI 4.0 and identification of requirements

In the future, production systems will consist of modular and flexible production components, being able to adapt to completely new manufacturing processes. This requirement arises from market turbulences caused by customer demands, i. e. highly customized goods in smaller production batches, or phenomenon like commercial crisis. In order to achieve adaptable production systems, one of the major challenges is to develop suitable autoconfiguration mechanisms for industrial automation systems. This paper presents a two-step architecture for the autoconfiguration of real-time Ethernet (RTE) systems. As a first step, an RTE-independent device discovery mechanism is introduced. Afterwards, it is shown how the parameters of an RTE can be configured automatically using Profinet IO as an exemplary RTE system. In contrast to the existing approaches, the proposed discovery mechanism is based on the OPC Unified Architecture (OPC-UA). In addition, a procedure to autoconfigure modular IO-Devices is introduced.

Henning Trsek

Papers

Control-as-a-service from the cloud: A case study for using virtualized PLCs

Clock Synchronization Over IEEE 802.11—A Survey of Methodologies and Protocols

Cloud computing for industrial automation systems — A comprehensive overview

Analysis of the Cyber-Security of industry 4.0 technologies based on RAMI 4.0 and identification of requirements

Using OPC-UA for the autoconfiguration of real-time Ethernet systems