Modellgestützter Entwurf von Feldgeräteapplikationen

Die Entwicklung von Feldgeräten ist ein äußerst komplexer Vorgang, welcher auf vielen Vorrausetzungen aufsetzt, diverse Anforderungen und Randbedingungen mitbringt und bisher wenig beachtet und veröffentlicht wurde. Angesichts der fortschreitenden Digitalisierung drängen immer mehr Anbieter auf den Automatisierungsmarkt. So sind aktuell zunehmend Technologien und Ansätze aus dem Umfeld des Internet of Things im Automatisierungsbereich zu finden. Diese Ansätze reichen von Sensoren ohne die in der Industrie üblichen Beschreibungen bis hin zu Marktplätzen, auf denen Integratoren und Anwender Softwareteile für Anlagen kaufen können. Für die neuen Anbieter, die häufig nicht aus dem klassischen Automatisierungsgeschäft kommen, sind die bisher bestehenden Modelle, Funktionalitäten, Profile und Beschreibungsmittel nicht immer leicht zu verwenden. So entstehen disruptive Lösungen auf Basis neu definierter Spezifikationen und Modelle. Trotz dieser Disruptivität sollte es das Ziel sein, die bewährten Automatisierungsfunktionen nicht neu zu erfinden, sondern diese effektiv und effizient in Abhängigkeit der Anforderungen auf unterschiedlichen Plattformen zu verwenden. Dies schließt ihre flexible Verteilung auf heterogene vernetzte Ressourcen explizit ein. Dabei können die Plattformen sowohl klassische Feldgeräte und Steuerungen sein, als auch normale Desktop-PCs und IoT-Knoten. Ziel dieser Arbeit ist es, eine Werkzeugkette für den modellbasierten Entwurf von Feldgeräteapplikationen auf Basis von Profilen und damit für den erweiterten Entwurf von verteilten Anlagenapplikationen zu entwickeln. Dabei müssen die verschiedenen Beschreibungsmöglichkeiten evaluiert werden, um diese mit detaillierten Parameter- und Prozessdatenbeschreibungen zu erweitern. Außerdem sollen modulare Konzepte genutzt und Vorbereitungen für die Verwendung von Semantik im Entwurfsprozess getroffen werden. In Bezug auf den Geräteengineeringprozess soll der Anteil des automatisierten Geräteengineerings erweitert werden. Dies soll zu einer Flexibilisierung der Geräteentwicklung führen, in der die Verschaltung der funktionalen Elemente beim Endkunden erfolgt. Auch das Deployment von eigenen funktionalen Elementen auf die Geräte der Hersteller soll durch den Endkunden möglich werden. Dabei wird auch eine automatisierte Erstellung von Gerätebeschreibungen benötigt. Alle diese Erweiterungen ermöglichen dann den letzten großen Schritt zu einer verteilten Applikation über heterogene Infrastrukturen. Dabei sind die funktionalen Elemente nicht nur durch die Gerätehersteller verteilbar, sondern diese können auch auf verschiedenen Plattformen unterschiedlicher Gerätehersteller verwendet werden. Damit einher geht die für aktuelle Entwicklungen wie Industrie 4.0 benötigte geräteunabhängige Definition von Funktionalität. Alle im Engineering entstandenen Informationen können dabei auf den unterschiedlichen Ebenen der Automatisierungspyramide und während des Lebenszyklus weiterverwendet werden. Eine Integration diverser Gerätefamilien außerhalb der Automatisierungstechnik wie z. B. IoT-Geräte und IT-Geräte ist damit vorstellbar. Nach einer Analyse der relevanten Techniken, Technologien, Konzepte, Methoden und Spezifikationen wurde eine Werkzeugkette für den modellgestützten Entwurf von Feldgeräten entwickelt und die benötigten Werkzeugteile und Erweiterungen an bestehenden Beschreibungen diskutiert. Dies Konzept wurde dann auf den verteilten Entwurf auf heterogener Hardware und heterogenen Plattformen erweitert, bevor beide Konzepte prototypisch umgesetzt und evaluiert wurden. Die Evaluation erfolgt an einem zweigeteilten Szenario aus der Sicht eines Geräteherstellers und eines Integrators. Die entwickelte Lösung integriert Ansätze aus dem Kontext von Industrie 4.0 und IoT. Sie trägt zu einer vereinfachten und effizienteren Automatisierung des Engineerings bei. Dabei können Profile als Baukasten für die Funktionalität der Feldgeräte und Anlagenapplikationen verwendet werden. Bestehende Beschränkungen im Engineering werden somit abgeschwächt, so dass eine Verteilung der Funktionalität auf heterogene Hardware und heterogene Plattformen möglich wird und damit zur Flexibilisierung der Automatisierungssysteme beiträgt.The development of field devices is a very complex procedure. Many preconditions need to be met. Various requirements and constrains need to be addressed. Beside this, there are only a few publications on this topic. Due to the ongoing digitalization, more and more solution providers are entering the market of the industrial automation. Technologies and approaches from the context of the Internet of Things are being used more and more in the automation domain. These approaches range from sensors without the typical descriptions from industry up to marketplaces where integrators and users can buy software components for plants. For new suppliers, who often do not come from the classical automation business, the already existing models, functionalities, profiles, and descriptions are not always easy to use. This results in disruptive solutions based on newly defined specifications and models. Despite this disruptiveness, the aim should be to prevent reinventing the proven automation functions, and to use them effectively, and efficiently on different platforms depending on the requirements. This explicitly includes the flexible distribution of the automation functions to heterogeneous networked resources. The platforms can be classical field devices and controllers, as well as normal desktop PCs and IoT nodes. The aim of this thesis is to develop a toolchain for the model-based design of field device applications based on profiles, and thus also suitable for the extended design of distributed plant applications. Therefore, different description methods are evaluated in order to enrich them with detailed descriptions of parameters and process data. Furthermore, c oncepts of modularity will also be used and preparations will be made for the use of semantics in the design process. With regard to the device engineering process, the share of automated device engineering will be increased. This leads to a flexibilisation of the device development, allowing the customer to perform the networking of the functional elements by himself. The customer should also be able to deploy his own functional elements to the manufacturers' devices. This requires an automated creation of device descriptions. Finally, all these extensions will enable a major step towards using a distributed application over heterogeneous infrastructures. Thus, the functional elements can not only be distributed by equipment manufacturers, but also be distributed on different platforms of different equipment manufacturers. This is accompanied by the device-independent definition of functionality required for current developments such as Industry 4.0. All information created during engineering can be used at different levels of the automation pyramid and throughout the life cycle. An integration of various device families from outside of Automation Technology, such as IoT devices and IT devices, is thus conceivable. After an analysis of the relevant techniques, technologies, concepts, methods, and specifications a toolchain for the model-based design of field devices was developed and the required tool parts, and extensions to existing descriptions were discussed. This concept was then extended to the distributed design on heterogeneous hardware and heterogeneous platforms. Finally, both concepts were prototypically implemented and evaluated. The evaluation is based on a two-part scenario from both the perspective of a device manufacturer, and the one of an integrator. The developed solution integrates approaches from the context of Industry 4.0 and IoT. It contributes to a simplified, and more efficient automation of engineering. Within this context, profiles can be used as building blocks for the functionality of field devices, and plant applications. Existing limitations in engineering are thus reduced, so that a distribution of functionality across heterogeneous hardware and heterogeneous platforms becomes possible and contributing to the flexibility of automation systems

Innovation landscape and challenges of smart technologies and systems - a European perspective

Latest developments in smart sensor and actuator technologies are expected to lead to a revolution in future manufacturing systems’ abilities and efficiency, often referred to as Industry 4.0. Smart technologies with higher degrees of autonomy will be essential to achieve the next breakthrough in both agility and productivity. However, the technologies will also bring substantial design and integration challenges and novelty risks to manufacturing businesses. The aim of this paper is to analyse the current landscape and to identify the challenges for introducing smart technologies into manufacturing systems in Europe. Expert knowledge from both industrial and academic practitioners in the field was extracted using an online survey. Feedback from a workshop was used to triangulate and extend the survey results. The findings indicate three main challenges for the ubiquitous implementation of smart technologies in manufacturing are: i) the perceived risk of novel technologies, ii) the complexity of integration, and iii) the consideration of human factors. Recommendations are made based on these findings to transform the landscape for smart manufacturing

A Knowledge Graph Based Integration Approach for Industry 4.0

The fourth industrial revolution, Industry 4.0 (I40) aims at creating smart factories employing among others Cyber-Physical Systems (CPS), Internet of Things (IoT) and Artificial Intelligence (AI). Realizing smart factories according to the I40 vision requires intelligent human-to-machine and machine-to-machine communication. To achieve this communication, CPS along with their data need to be described and interoperability conflicts arising from various representations need to be resolved. For establishing interoperability, industry communities have created standards and standardization frameworks. Standards describe main properties of entities, systems, and processes, as well as interactions among them. Standardization frameworks classify, align, and integrate industrial standards according to their purposes and features. Despite being published by official international organizations, different standards may contain divergent definitions for similar entities. Further, when utilizing the same standard for the design of a CPS, different views can generate interoperability conflicts. Albeit expressive, standardization frameworks may represent divergent categorizations of the same standard to some extent, interoperability conflicts need to be resolved to support effective and efficient communication in smart factories. To achieve interoperability, data need to be semantically integrated and existing conflicts conciliated. This problem has been extensively studied in the literature. Obtained results can be applied to general integration problems. However, current approaches fail to consider specific interoperability conflicts that occur between entities in I40 scenarios. In this thesis, we tackle the problem of semantic data integration in I40 scenarios. A knowledge graphbased approach allowing for the integration of entities in I40 while considering their semantics is presented. To achieve this integration, there are challenges to be addressed on different conceptual levels. Firstly, defining mappings between standards and standardization frameworks; secondly, representing knowledge of entities in I40 scenarios described by standards; thirdly, integrating perspectives of CPS design while solving semantic heterogeneity issues; and finally, determining real industry applications for the presented approach. We first devise a knowledge-driven approach allowing for the integration of standards and standardization frameworks into an Industry 4.0 knowledge graph (I40KG). The standards ontology is used for representing the main properties of standards and standardization frameworks, as well as relationships among them. The I40KG permits to integrate standards and standardization frameworks while solving specific semantic heterogeneity conflicts in the domain. Further, we semantically describe standards in knowledge graphs. To this end, standards of core importance for I40 scenarios are considered, i.e., the Reference Architectural Model for I40 (RAMI4.0), AutomationML, and the Supply Chain Operation Reference Model (SCOR). In addition, different perspectives of entities describing CPS are integrated into the knowledge graphs. To evaluate the proposed methods, we rely on empirical evaluations as well as on the development of concrete use cases. The attained results provide evidence that a knowledge graph approach enables the effective data integration of entities in I40 scenarios while solving semantic interoperability conflicts, thus empowering the communication in smart factories

Internet of Things Based Technology for Smart Home System: A Generic Framework

Internet of Things (IoT) is a technology which enables computing devices, physical and virtual objects/devices to be connected to the internet so that users can control and monitor devices. The IoT offers huge potential for development of various applications namely: e-governance, environmental monitoring, military applications, infrastructure management, industrial applications, energy management, healthcare monitoring, home automation and transport systems. In this paper, the brief overview of existing frameworks for development of IoT applications, techniques to develop smart home applications using existing IoT frameworks, and a new generic framework for the development of IoTbasedsmart home system is presented. The proposed generic framework comprises various modules such as Auto-Configuration and Management, Communication Protocol, Auto-Monitoring and Control, and Objects Access Control. The architecture of the new generic framework and the functionality of various modules in the framework are also presented. The proposed generic framework is helpful for making every house as smart house to increase the comfort of inhabitants. Each of the components of generic framework is robust in nature in providing services at any time. The components of smart home system are designed to take care of various issues such as scalability, interoperability, device adaptability, security and privacy. The proposed generic framework is designed to work on all vendor boards and variants of Linux and Windows operating system

Virtual engineering and commissioning to support the lifecycle of a manufacturing assembly system

Prior to the physical build of the industrial automation system, some challenges arise, such as processes’ cycle times calculations, ergonomics and safety evaluation, and the integration of separate machines to the complete production shops. This, in turn, requires reconfiguring the processes and component parameters. As a result, the lifecycle of the system development is prolonged, and the potential for erroneous performance increases. In modern digital manufacturing environments, virtual engineering (VE) and virtual commissioning (VC) serve as effective tools to tackle the aforementioned problems and their consequences. The virtual models developed for VE and VC not only assist system developers in the physical build stage but also in the following stages of the system lifecycle by providing a common virtual model, a digital twin (DT), of the manufacturing processes and the product. This developed model should possess the ability to simulate the system behaviour, e.g., the mechanics, kinematics, speed and acceleration profiles. Three stakeholders are involved in the development process: the machine builder, system integrator and end user. The current work focuses on the virtual engineering approach to support the entire lifecycle of a manufacturing system from the machine builder, system integrator and end user perspectives. For this purpose, it puts forward a systematic methodology of implementing VC and VE using a toolset developed by the Automation Systems Group at the University of Warwick within an industrial project. The suggested methodology is illustrated in a case study where a digital twin of a physical station was modelled, developed and tested in parallel with the physical machine development and build. Finally, the benefits and limitations are highlighted based on the gained outcomes and the implemented activities

Comprehensive Survey on the Techniques used in Weighing and Recording Systems

Today farmers are facing more problems about fruit’s weight measuring and recording at the time of their final cost calculation while selling to the agents. Now a day, weighing issues are the most important in concern with the issues of farmers everywhere in the agriculture field, so weighing of everything from farm gains higher and higher importance in recent years. Here in this paper, trying to introduce the comprehensive literature study related to the various measuring systems that are necessary in the fields such as agriculture, industries and market. Weighing and measuring where possibilities of incursion are increasing day by day. In past days, the research is gone on various weighing and measuring systems, which provided the solution to manual methods. Due to the advancement in recent techniques, some weighing systems are based on microcontroller, ARM11, dynamic, fuzzy-logic, force-sensing, image-processing, filter, online, sensor network, and LVDT based etc. Every system has its own advantages and disadvantages. In most of systems, strain gauge technique is used for weighing so the system will become cost effective, more reliable and it will take less time to stores the many reading for continuous measuring process. The weight measuring systems today needs to make use of the latest technology. In some papers, the authors have presented weighing systems based on embedded and PLC and sometimes the load sensors is connected by online and sensor network. Hence, it could not easily hack the data of weighing records by hackers. A lot of modification takes places in various weighing and recording systems from the last few years, in next coming years many changes will takes place

Methods for Semantic Interoperability in AutomationML-based Engineering

Industrial engineering is an interdisciplinary activity that involves human experts from various technical backgrounds working with different engineering tools. In the era of digitization, the engineering process generates a vast amount of data. To store and exchange such data, dedicated international standards are developed, including the XML-based data format AutomationML (AML). While AML provides a harmonized syntax among engineering tools, the semantics of engineering data remains highly heterogeneous. More specifically, the AML models of the same domain or entity can vary dramatically among different tools that give rise to the so-called semantic interoperability problem. In practice, manual implementation is often required for the correct data interpretation, which is usually limited in reusability. Efforts have been made for tackling the semantic interoperability problem. One mainstream research direction has been focused on the semantic lifting of engineering data using Semantic Web technologies. However, current results in this field lack the study of building complex domain knowledge that requires a profound understanding of the domain and sufficient skills in ontology building. This thesis contributes to this research field in two aspects. First, machine learning algorithms are developed for deriving complex ontological concepts from engineering data. The induced concepts encode the relations between primitive ones and bridge the semantic gap between engineering tools. Second, to involve domain experts more tightly into the process of ontology building, this thesis proposes the AML concept model (ACM) for representing ontological concepts in a native AML syntax, i.e., providing an AML-frontend for the formal ontological semantics. ACM supports the bidirectional information flow between the user and the learner, based on which the interactive machine learning framework AMLLEARNER is developed. Another rapidly growing research field devotes to develop methods and systems for facilitating data access and exchange based on database theories and techniques. In particular, the so-called Query By Example (QBE) allows the user to construct queries using data examples. This thesis adopts the idea of QBE in AML-based engineering by introducing the AML Query Template (AQT). The design of AQT has been focused on a native AML syntax, which allows constructing queries with conventional AML tools. This thesis studies the theoretical foundation of AQT and presents algorithms for the automated generation of query programs. Comprehensive requirement analysis shows that the proposed approach can solve the problem of semantic interoperability in AutomationML-based engineering to a great extent

Secure and safe virtualization-based framework for embedded systems development

Tese de Doutoramento - Programa Doutoral em Engenharia Electrónica e de Computadores (PDEEC)The Internet of Things (IoT) is here. Billions of smart, connected devices are proliferating at rapid pace in our key infrastructures, generating, processing and exchanging vast amounts of security-critical and privacy-sensitive data. This strong connectivity of IoT environments demands for a holistic, end-to-end security approach, addressing security and privacy risks across different abstraction levels: device, communications, cloud, and lifecycle managment. Security at the device level is being misconstrued as the addition of features in a late stage of the system development. Several software-based approaches such as microkernels, and virtualization have been used, but it is proven, per se, they fail in providing the desired security level. As a step towards the correct operation of these devices, it is imperative to extend them with new security-oriented technologies which guarantee security from the outset. This thesis aims to conceive and design a novel security and safety architecture for virtualized systems by 1) evaluating which technologies are key enablers for scalable and secure virtualization, 2) designing and implementing a fully-featured virtualization environment providing hardware isolation 3) investigating which "hard entities" can extend virtualization to guarantee the security requirements dictated by confidentiality, integrity, and availability, and 4) simplifying system configurability and integration through a design ecosystem supported by a domain-specific language. The developed artefacts demonstrate: 1) why ARM TrustZone is nowadays a reference technology for security, 2) how TrustZone can be adequately exploited for virtualization in different use-cases, 3) why the secure boot process, trusted execution environment and other hardware trust anchors are essential to establish and guarantee a complete root and chain of trust, and 4) how a domain-specific language enables easy design, integration and customization of a secure virtualized system assisted by the above mentioned building blocks.Vivemos na era da Internet das Coisas (IoT). Biliões de dispositivos inteligentes começam a proliferar nas nossas infraestruturas chave, levando ao processamento de avolumadas quantidades de dados privados e sensíveis. Esta forte conectividade inerente ao conceito IoT necessita de uma abordagem holística, em que os riscos de privacidade e segurança são abordados nas diferentes camadas de abstração: dispositivo, comunicações, nuvem e ciclo de vida. A segurança ao nível dos dispositivos tem sido erradamente assegurada pela inclusão de funcionalidades numa fase tardia do desenvolvimento. Têm sido utilizadas diversas abordagens de software, incluindo a virtualização, mas está provado que estas não conseguem garantir o nível de segurança desejado. De forma a garantir a correta operação dos dispositivos, é fundamental complementar os mesmos com novas tecnologias que promovem a segurança desde os primeiros estágios de desenvolvimento. Esta tese propõe, assim, o desenvolvimento de uma solução arquitetural inovadora para sistemas virtualizados seguros, contemplando 1) a avaliação de tecnologias chave que promovam tal realização, 2) a implementação de uma solução de virtualização garantindo isolamento por hardware, 3) a identificação de componentes que integrados permitirão complementar a virtualização para garantir os requisitos de segurança, e 4) a simplificação do processo de configuração e integração da solução através de um ecossistema suportado por uma linguagem de domínio específico. Os artefactos desenvolvidos demonstram: 1) o porquê da tecnologia ARM TrustZone ser uma tecnologia de referência para a segurança, 2) a efetividade desta tecnologia quando utilizada em diferentes domínios, 3) o porquê do processo seguro de inicialização, juntamente com um ambiente de execução seguro e outros componentes de hardware, serem essenciais para estabelecer uma cadeia de confiança, e 4) a viabilidade em utilizar uma linguagem de um domínio específico para configurar e integrar um ambiente virtualizado suportado pelos artefactos supramencionados

How data will transform industrial processes: crowdsensing, crowdsourcing and big data as pillars of industry 4.0

We are living in the era of the fourth industrial revolution, namely Industry 4.0. This paper presents themain aspects related to Industry 4.0, the technologies thatwill enable this revolution, and the main application domains thatwill be affected by it. The effects that the introduction of Internet of Things (IoT), Cyber-Physical Systems (CPS), crowdsensing, crowdsourcing, cloud computing and big data will have on industrial processeswill be discussed. Themain objectiveswill be represented by improvements in: production efficiency, quality and cost-effectiveness; workplace health and safety, as well as quality of working conditions; products' quality and availability, according to mass customisation requirements. The paper will further discuss the common denominator of these enhancements, i.e., data collection and analysis. As data and information will be crucial for Industry 4.0, crowdsensing and crowdsourcing will introduce new advantages and challenges, which will make most of the industrial processes easier with respect to traditional technologies