Interoperability middleware for IIoT gateways based on international standard ontologies and standardized digital representation

Recent advances in the areas of microelectronics, information technology, and communication protocols have made the development of smaller devices with greater processing capacity and lower energy consumption. This context contributed to the growing number of physical devices in industrial environments which are interconnected and communicate via the internet, enabling concepts such as Industry 4.0 and the Industrial Internet of Things (IIoT). These nodes have different sensors and actuators that monitor and control environment data. Several companies develop these devices, including diverse communication protocols, data structures, and IoT platforms, which leads to interoperability issues. In IoT scenarios, interoperability is the ability of two systems to communicate and share services. Therefore, communication problems can make it unfeasible to use heterogeneous devices, increasing the project’s financial cost and development time. In an industry, interoperability is related to different aspects, such as physical communication, divergent device communication protocols, and syntactical problems, referring to the distinct data structure. Developing a new standard for solving these matters may bring interoperability-related drawbacks rather than effectively solving these issues. Therefore, to mitigate interoperability problems in industrial applications, this work proposes the development of an interoperability middleware for Edge-enabled IIoT gateways based on international standards. The middleware is responsible for translating communication protocols, updating data from simulations or physical nodes to the assets’ digital representations, and storing data locally or remotely. The middleware adopts the IEEE industrial standard ontologies combined with assets’ standardized digital models. As a case study, a simulation replicates the production of a nutrient solution for agriculture, controlled by IIoT nodes. The use case consists of three devices, each equipped with at least five sensors or actuators, communicating in different communication protocols and exchanging data using diverse structures. The performance of the proposed middleware and its proposed translations algorithms were evaluated, obtaining satisfactory results for mitigating interoperable in industrial applications.Devido a recentes avanços nas áreas de microeletrônica, tecnologia da informação, e protocolos de comunicação tornaram possível o desenvolvimento de dispositivos cada vez menores com maior capacidade de processamento e menor consumo energético. Esse contexto contribuiu para o crescente nú- mero desses dispositivos na industria que estão interligados via internet, viabilizando conceitos como Indústria 4.0 e Internet das Coisas Industrial (IIoT). Esses nós possuem diferentes sensores e atuadores que monitoram e controlam os dados do ambiente. Esses equipamentos são desenvolvidos por diferentes empresas, incluindo protocolos de comunicação, estruturas de dados e plataformas de IoT distintos, acarretando em problemas de interoperabilidade. Em cenários de IoT, interoperabilidade, é a capacidade de sistemas se comunicarem e compartilharem serviços. Portanto, esses problemas podem inviabilizar o uso de dispositivos heterogêneos, aumentando o custo financeiro do projeto e seu tempo de desenvolvimento. Na indústria, interoperabilidade se divide em diferentes aspectos, como comunicação e problemas sintáticos, referentes à estrutura de dados distinta. O desenvolvimento de um padrão industrial pode trazer mais desvantagens relacionadas à interoperabilidade, em vez de resolver esses problemas. Portanto, para mitigar problemas relacionados a intoperabilidade industrial, este trabalho propõe o desenvolvimento de um middleware de interoperável para gateways IIoT baseado em padrões internacionais e ontologias. O middleware é responsável por traduzir diferentes protocolos de comunicação, atualizar os dados dos ativos industriais por meio de suas representações digitais, esses armazenados localmente ou remotamente. O middleware adota os padrões ontológicos industriais da IEEE combinadas com modelos digitais padronizados de ativos industriais. Como estudo de caso, são realizadas simulações para a produção de uma solução nutritiva para agricultura, controlada por nós IIoT. O processo utiliza três dispositivos, cada um equipado com pelo menos cinco sensores ou atuadores, por meio de diferentes protocolos de comunicação e estruturas de dados. O desempenho do middleware proposto e seus algoritmos de tradução foram avaliados e apresentados no final do trabalho, os quais resultados foram satisfatórios para mitigar a interoperabilidade em aplicações industriais

Replacing internal communication protocol in UNIC control system

This thesis examines OPC-UA (Open Platform Communications Unified Architecture) and investigate how it could be used in Wärtsilä for performing internal communication on their UNIC engine control system. Features of OPC-UA are compared to the currently used in-house built protocol to find out if changing the protocol would be feasible. OPC-UA is a communication specification that standardizes information exchange of industrial automation. This thesis introduces the key concepts of the specification such as information modelling, client-server communication model, publish-subscribe communication model, and the available transportation mappings defining the concrete protocols for transportation. In addition, the current communication implementation of the control system and the services provided for system software components are inspected. After inspections, a general mapping is made between the currently provided services and the OPC-UA features. It is also discussed what transportation protocols shall be chosen for OPC-UA. The objective of the thesis is to list requirements for performing internal communication by using OPC-UA. Requirements are set for the OPC-UA software development kit features based on the mapped services and protocols. The mapped protocols also introduce requirements for the network stack of the platform software. Based on the feature mappings an architectural proposal for OPC-UA implementation on the control system is presented. It is shown how the different OPC-UA software components could be distributed between the different hardware modules of the system, how the information model and communication interfaces could be initialized in the source code, and how the servers of the different hardware modules could be aggregated into a single server. It is also presented how the information model of the control system could be structured. A short performance comparison is performed by comparing the data frame structure of the current implementation and the mapped counterpart. Finally, it is concluded that in theory OPC UA is feasible for performing the internal communication as it provides a lot of options for implementing the tasks of the current service handlers, but in practice the change contains some risks such as immaturity of the technology. Furthermore, the change would require a lot of work, and it could be questioned if the business value of the protocol change is worth the investment.Tässä opinnäytetyössä tarkastellaan OPC-UA:ta (Open Platform Communications Unified Architecture), ja selvitetään miten OPC-UA-tiedonsiirtoa voitaisiin käyttää Wärstilän UNIC-moottorinohjausjärjestelmän sisäisen tiedonsiirron suorittamiseen. OPC-UA ominaisuuksia verrataan tällä hetkellä käytössä olevaan yrityksen itse valmistamaan protokollaan, jotta saadaan selville, olisiko protokollan vaihtaminen mahdollista. OPC-UA on tietoliikennespesifikaatio, joka standardoi teollisen automaation tiedonvaihdon. Tässä opinnäytetyössä esitellään spesifikaation keskeisimmät käsitteet kuten tiedon mallintaminen, asiakas-palvelin-viestintämalli, julkaise-tilaa-viestintämalli sekä käytettävissä olevat tiedon siirtomenetelmät, jotka määrittelevät konkreettiset tiedonsiirtoon käytettävät protokollat. Tarkasteltavana on myös ohjausjärjestelmän nykyinen viestintätoteutus ja sen tarjoamat palvelut järjestelmän eri ohjelmistokomponenteille. Tarkastusten jälkeen tehdään yleinen kartoitus tämänhetkisten palvelujen ja OPC-UA:n ominaisuuksien välille. Opinnäytetyön tavoitteena on listata vaatimukset sisäisen viestinnän suorittamiselle OPC-UA:n avulla. Käytettävälle OPC-UA-ohjelmistokehityspaketille asetetaan vaatimukset kartoitettujen palvelujen ja protokollien perusteella. OPC-UA:n tarjoamat protokollat asettavat myös vaatimuksia alustaohjelmiston verkkopinolle. Ominaisuuskartoitusten perusteella esitetään myös arkkitehtoninen ehdotelma OPC-UA:n toteuttamiselle ohjausjärjestelmässä. Ehdotelma osoittaa, kuinka eri OPC-UA-ohjelmistokomponentit voitaisiin jakaa järjestelmän eri laitteistomoduulien kesken, miten tietomalli ja tietoliikennerajapinnat voidaan alustaa lähdekoodissa ja kuinka eri moduulien palvelimet voitaisiin yhdistää yhdeksi palvelimeksi. Lisäksi esitetään miten järjestelmän tietomalli voisi rakentua. Lyhyt teoreettinen suorituskykyvertailu suoritetaan vertaamalla nykyisen toteutuksen datakehysrakennetta ja kartoitettua vastinetta. Lopuksi todetaan, että teoriassa OPC-UA on käyttökelpoinen sisäisen viestinnän suorittamiseen, koska se tarjoaa paljon vaihtoehtoja nykyisten palvelunkäsittelijöiden tehtävien toteuttamiseen. Käytännössä muutokseen sisältyy kuitenkin riskejä, kuten tekniikan tuoreuteen liittyvä epäkypsyys. Muutos vaatisi paljon työtä ja protokollamuutoksen tuottama liikearvo on hieman kyseenalainen verrattuna vaadittuun investointiin

INDUSTRIAL DEVICE INTEGRATION AND VIRTUALIZATION FOR SMART FACTORIES

Given the constant industry growth and modernization, several technologies have been introduced in the shop floor, in particular regarding industrial devices. Each device brand and model usually requires different interfaces and communication protocols, a technological diversity which renders the automatic interconnection with production management software extremely challenging. However, combining key technologies such as machine monitoring, digital twin and virtual commissioning, along with a complete communication protocol like OPC UA, it is possible to contribute towards industrial device integration on a Smart Factory environment. To achieve this goal, several methodologies and a set of tools were defined. This set of tools, as well as facilitating the integration tasks, should also be part of a virtual engineering environment, sharing the same virtual model, the digital twin, through the complete lifecycle of the industrial device, namely the project, simulation, implementation and execution/monitoring/supervision and, eventually, decommissioning phases. A key result of this work is the development of a set of virtual engineering tools and methodologies based on OPC UA communication, with the digital twin implemented using RobotStudio, in order to accomplish the complete lifecycle support of an industrial device, from the project and simulation phases, to monitoring and supervision, suitable for integration in Industry 4.0 factories. To evaluate the operation of the developed set of tools, experiments were performed for a test scenario with different devices. Other relevant result is related with the integration of a specific industrial device – CNC machining equipment. Given the variety of monitoring systems and communication protocols, an approach where various solutions available on the market are combined on a single system is followed. These kinds of all-in-one solutions would give production managers access to the information necessary for a continuous monitoring and improvement of the entire production process

A Framework for Industry 4.0

The potential of the Industry 4.0 will allow the national industry to develop all kinds of procedures, especially in terms of competitive differentiation. The prospects and motivations behind Industry 4.0 are related to the management that is essentially geared towards industrial internet, to the integrated analysis and use of data, to the digitalization of products and services, to new disruptive business models and to the cooperation within the value chain. It is through the integration of Cyber-Physical Systems (CPS), into the maintenance process that it is possible to carry out a continuous monitoring of industrial machines, as well as to apply advanced techniques for predictive and proactive maintenance. The present work is based on the MANTIS project, aiming to construct a specific platform for the proactive maintenance of industrial machines, targeting particularly the case of GreenBender ADIRA Steel Sheet. In other words, the aim is to reduce maintenance costs, increase the efficiency of the process and consequently the profit. Essentially, the MANTIS project is a multinational research project, where the CISTER Research Unit plays a key role, particularly in providing the communications infrastructure for one MANTIS Pilot. The methodology is based on a follow-up study, which is jointly carried with the client, as well as within the scope of the implementation of the ADIRA Pilot. The macro phases that are followed in the present work are: 1) detailed analysis of the business needs; 2) preparation of the architecture specification; 3) implementation/development; 4) tests and validation; 5) support; 6) stabilization; 7) corrective and evolutionary maintenance; and 8) final project analysis and corrective measures to be applied in future projects. The expected results of the development of such project are related to the integration of the industrial maintenance process, to the continuous monitoring of the machines and to the application of advanced techniques of preventive and proactive maintenance of industrial machines, particularly based on techniques and good practices of the Software Engineering area and on the integration of Cyber-Physical Systems.O potencial desenvolvido pela Indústria 4.0 dotará a indústria nacional de capacidades para desenvolver todo o tipo de procedimentos, especialmente a nível da diferenciação competitiva. As perspetivas e as motivações por detrás da Indústria 4.0 estão relacionadas com uma gestão essencialmente direcionada para a internet industrial, com uma análise integrada e utilização de dados, com a digitalização de produtos e de serviços, com novos modelos disruptivos de negócio e com uma cooperação horizontal no âmbito da cadeia de valor. É através da integração dos sistemas ciber-físicos no processo de manutenção que é possível proceder a um monitoramento contínuo das máquinas, tal como à aplicação de técnicas avançadas para a manutenção preditiva e pró-ativa das mesmas. O presente trabalho é baseado no projeto MANTIS, objetivando, portanto, a construção de uma plataforma específica para a manutenção pró-ativa das máquinas industriais, neste caso em concreto das prensas, que serão as máquinas industriais analisadas ao longo do presente trabalho. Dito de um outro modo, objetiva-se, através de uma plataforma em específico, reduzir todos os custos da sua manutenção, aumentando, portanto, os lucros industriais advindos da produção. Resumidamente, o projeto MANTIS consiste num projeto de investigação multinacional, onde a Unidade de Investigação CISTER desenvolve um papel fundamental, particularmente no fornecimento da infraestrutura de comunicação no Piloto MANTIS. A metodologia adotada é baseada num estudo de acompanhamento, realizado em conjunto com o cliente, e no âmbito da implementação do Piloto da ADIRA. As macro fases que são compreendidas por esta metodologia, e as quais serão seguidas, são: 1) análise detalhada das necessidades de negócio; 2) preparação da especificação da arquitetura; 3) implementação/desenvolvimento; 4) testes e validação; 5) suporte; 6) estabilização; 7) manutenção corretiva e evolutiva; e 8) análise final do projeto e medidas corretivas a aplicar em projetos futuros. Os resultados esperados com o desenvolvimento do projeto estão relacionados com a integração do processo de manutenção industrial, a monitorização contínua das máquinas e a aplicação de técnicas avançadas de manutenção preventiva e pós-ativa das máquinas, especialmente com base em técnicas e boas práticas da área de Engenharia de Software

Towards a Unified and Robust Data-Driven Approach. A Digital Transformation of Production Plants in the Age of Industry 4.0

Nowadays, industrial companies are engaging their global transition toward the fourth industrial revolution (the so-called Industry 4.0). The main objective is to increase the Overall Equipment Effectiveness (OEE), by collecting, storing and analyzing production data. Several challenges have to be tackled to propose a unified data-driven approach to rely on, from the low-layers data collection on the machine production lines using Operational Technologies (OT), to the monitoring and more importantly the analysis of the data using Information Technologies (IT). This is all the more important for companies having decades of existence – as Cebi Luxembourg S.A., our partner in a Research, Development and Innovation project subsidised by the ministry of the Economy in Luxembourg – to upgrade their on-site technologies and move towards new business models. Artificial Intelligence (AI) now knows a real interest from industrial actors and becomes a cornerstone technology for helping humans in decision-making and data-analysis tasks, thanks to the huge amount of (sensors-based) univariate time-series available in the production floor. However, such amount of data is not sufficient for AI to work properly and to make right decisions. This also requires a good data quality. Indeed, good theoretical performance and high accuracy can be obtained when trained and tested in isolation, but AI models may still provide degraded performance in real/industrial conditions. In that context, the problem is twofold: • Industrial production systems are vertically-oriented closed systems that make difficult their communication and their cooperation with each other, and intrinsically the data collection. • Industrial companies used to implement deterministic processes. Introducing AI - that can be classified as stochastic - in the industry requires a full understanding of the potential deviation of the models in order to be aware of their domain of validity. This dissertation proposes a unified strategy for digitizing an industrial system and methods for evaluating the performance and the robustness of AI models that can be used in such data-driven production plants. In the first part of the dissertation, we propose a three-steps strategy to digitize an industrial system, called TRIDENT, that enables industrial actors to implement data collection on production lines, and in fine to monitor in real-time the production plant. Such strategy has been implemented and evaluated on a pilot case-study at Cebi Luxembourg S.A. Three protocols (OPC-UA, MQTT and O-MI/O-DF) are used for investigating their impact on the real-time performance. The results show that, even if these protocols have some disparity in terms of performance, they are suitable for an industrial deployment. This strategy has now been extended and implemented by our partner - Cebi Luxembourg S.A - in its production environment. In the second part of the thesis dissertation, we aim at investigating the robustness of AI models in industrial settings. We then propose a systematic approach to evaluate the robustness under perturbations. Assuming that i) real perturbations - in particular on the data collection - cannot be recorded or generated in real industrial environment (that could lead to production stops) and ii) a model would not be implemented before evaluating its potential deviations, limits or weaknesses, our approach is based on artificial injections of perturbations into the data sets, and is evaluated on state-of-the-art classifiers (both Machine-Learning and Deep-Learning) and data sets (in particular, public sensors-based univariate time series). First, we propose a coarse-grained study, with two artificial perturbations - called swapping effect and dropping effect - in which simple random algorithms are used. This already highlights a great disparity of the models’ robustness under such perturbations that industrial actors need to be aware of. Second, we propose a fine-grained study where instead of testing randomly some parameters' values, we used Genetic Algorithms to look for the models' limits. To do so, we define our multi-objectives optimisation problem with a fitness function as: maximising the impact of the perturbations (i.e. decreasing the most the model's accuracy), while minimising the changes in the time-series (with regards to our two parameters). This can be seen as an adversarial case, where the goal is not to exploit these weaknesses in a malicious way but to be aware of. Based on such a study, methods for making more robust the model and/or for observing such behaviour on the infrastructure could be investigated and implemented if needed. The tool developed in this latter study is therefore ready for being used in a real industrial case, where data sets and perturbations can now be fitted to the scenario

D7.2 - Report on first External Liaisons Workshop

This deliverable provides a report on the "2nd International Workshop on Interoperability and Open Source Solutions for the Internet of Things”, co-located with the IoT 2016 conference, in Stuttgart, Germany, on November 7, 2016

Distributed Planning for Self-Organizing Production Systems

Für automatisierte Produktionsanlagen gibt es einen fundamentalen Tradeoff zwischen Effizienz und Flexibilität. In den meisten Fällen sind die Abläufe nicht nur durch den physischen Aufbau der Produktionsanlage, sondern auch durch die spezielle zugeschnittene Programmierung der Anlagensteuerung fest vorgegeben. Änderungen müssen aufwändig in einer Vielzahl von Systemen nachgezogen werden. Das macht die Herstellung kleiner Stückzahlen unrentabel. In dieser Dissertation wird ein Ansatz entwickelt, um eine automatische Anpassung des Verhaltens von Produktionsanlagen an wechselnde Aufträge und Rahmenbedingungen zu erreichen. Dabei kommt das Prinzip der Selbstorganisation durch verteilte Planung zum Einsatz. Die aufeinander aufbauenden Ergebnisse der Dissertation sind wie folgt: 1. Es wird ein Modell von Produktionsanlagen entwickelt, dass nahtlos von der detaillierten Betrachtung physikalischer Produktionsprozesse bis hin zu Lieferbeziehungen zwischen Unternehmen skaliert. Im Vergleich zu existierenden Modellen von Produktionsanlagen werden weniger limitierende Annahmen gestellt. In diesem Sinne ist der Modellierungsansatz ein Kandidat für eine häufig geforderte "Theorie der Produktion". 2. Für die so modellierten Szenarien wird ein Algorithmus zur Optimierung der nebenläufigen Abläufe entwickelt. Der Algorithmus verbindet Techniken für die kombinatorische und die kontinuierliche Optimierung: Je nach Detailgrad und Ausgestaltung des modellierten Szenarios kann der identische Algorithmus kombinatorische Fertigungsfeinplanung (Scheduling) vornehmen, weltweite Lieferbeziehungen unter Einbezug von Unsicherheiten und Risiko optimieren und physikalische Prozesse prädiktiv regeln. Dafür werden Techniken der Monte-Carlo Baumsuche (die auch bei Deepminds Alpha Go zum Einsatz kommen) weiterentwickelt. Durch Ausnutzung zusätzlicher Struktur in den Modellen skaliert der Ansatz auch auf große Szenarien. 3. Der Planungsalgorithmus wird auf die verteilte Optimierung durch unabhängige Agenten übertragen. Dafür wird die sogenannte "Nutzen-Propagation" als Koordinations-Mechanismus entwickelt. Diese ist von der Belief-Propagation zur Inferenz in Probabilistischen Graphischen Modellen inspiriert. Jeder teilnehmende Agent hat einen lokalen Handlungsraum, in dem er den Systemzustand beobachten und handelnd eingreifen kann. Die Agenten sind an der Maximierung der Gesamtwohlfahrt über alle Agenten hinweg interessiert. Die dafür notwendige Kooperation entsteht über den Austausch von Nachrichten zwischen benachbarten Agenten. Die Nachrichten beschreiben den erwarteten Nutzen für ein angenommenes Verhalten im Handlungsraum beider Agenten. 4. Es wird eine Beschreibung der wiederverwendbaren Fähigkeiten von Maschinen und Anlagen auf Basis formaler Beschreibungslogiken entwickelt. Ausgehend von den beschriebenen Fähigkeiten, sowie der vorliegenden Aufträge mit ihren notwendigen Produktionsschritten, werden ausführbare Aktionen abgeleitet. Die ausführbaren Aktionen, mit wohldefinierten Vorbedingungen und Effekten, kapseln benötigte Parametrierungen, programmierte Abläufe und die Synchronisation von Maschinen zur Laufzeit. Die Ergebnisse zusammenfassend werden Grundlagen für flexible automatisierte Produktionssysteme geschaffen -- in einer Werkshalle, aber auch über Standorte und Organisationen verteilt -- welche die ihnen innewohnenden Freiheitsgrade durch Planung zur Laufzeit und agentenbasierte Koordination gezielt einsetzen können. Der Bezug zur Praxis wird durch Anwendungsbeispiele hergestellt. Die Machbarkeit des Ansatzes wurde mit realen Maschinen im Rahmen des EU-Projekts SkillPro und in einer Simulationsumgebung mit weiteren Szenarien demonstriert

Kommunikation und Bildverarbeitung in der Automation

In diesem Open-Access-Tagungsband sind die besten Beiträge des 9. Jahreskolloquiums "Kommunikation in der Automation" (KommA 2018) und des 6. Jahreskolloquiums "Bildverarbeitung in der Automation" (BVAu 2018) enthalten. Die Kolloquien fanden am 20. und 21. November 2018 in der SmartFactoryOWL, einer gemeinsamen Einrichtung des Fraunhofer IOSB-INA und der Technischen Hochschule Ostwestfalen-Lippe statt. Die vorgestellten neuesten Forschungsergebnisse auf den Gebieten der industriellen Kommunikationstechnik und Bildverarbeitung erweitern den aktuellen Stand der Forschung und Technik. Die in den Beiträgen enthaltenen anschaulichen Beispiele aus dem Bereich der Automation setzen die Ergebnisse in den direkten Anwendungsbezug

A Common Digital Twin Platform for Education, Training and Collaboration

The world is in transition driven by digitalization; industrial companies and educational institutions are adopting Industry 4.0 and Education 4.0 technologies enabled by digitalization. Furthermore, digitalization and the availability of smart devices and virtual environments have evolved to pro- duce a generation of digital natives. These digital natives whose smart devices have surrounded them since birth have developed a new way to process information; instead of reading literature and writing essays, the digital native generation uses search engines, discussion forums, and on- line video content to study and learn. The evolved learning process of the digital native generation challenges the educational and industrial sectors to create natural training, learning, and collaboration environments for digital natives. Digitalization provides the tools to overcome the aforementioned challenge; extended reality and digital twins enable high-level user interfaces that are natural for the digital natives and their interaction with physical devices. Simulated training and education environments enable a risk-free way of training safety aspects, programming, and controlling robots. To create a more realistic training environment, digital twins enable interfacing virtual and physical robots to train and learn on real devices utilizing the virtual environment. This thesis proposes a common digital twin platform for education, training, and collaboration. The proposed solution enables the teleoperation of physical robots from distant locations, enabling location and time-independent training and collaboration in robotics. In addition to teleoperation, the proposed platform supports social communication, video streaming, and resource sharing for efficient collaboration and education. The proposed solution enables research collaboration in robotics by allowing collaborators to utilize each other’s equipment independent of the distance between the physical locations. Sharing of resources saves time and travel costs. Social communication provides the possibility to exchange ideas and discuss research. The students and trainees can utilize the platform to learn new skills in robotic programming, controlling, and safety aspects. Cybersecurity is considered from the planning phase to the implementation phase. Only cybersecure methods, protocols, services, and components are used to implement the presented platform. Securing the low-level communication layer of the digital twins is essential to secure the safe teleoperation of the robots. Cybersecurity is the key enabler of the proposed platform, and after implementation, periodic vulnerability scans and updates enable maintaining cybersecurity. This thesis discusses solutions and methods for cyber securing an online digital twin platform. In conclusion, the thesis presents a common digital twin platform for education, training, and collaboration. The presented solution is cybersecure and accessible using mobile devices. The proposed platform, digital twin, and extended reality user interfaces contribute to the transitions to Education 4.0 and Industry 4.0

Modeling and Simulation Methodologies for Digital Twin in Industry 4.0

The concept of Industry 4.0 represents an innovative vision of what will be the factory of the future. The principles of this new paradigm are based on interoperability and data exchange between dierent industrial equipment. In this context, Cyber- Physical Systems (CPSs) cover one of the main roles in this revolution. The combination of models and the integration of real data coming from the field allows to obtain the virtual copy of the real plant, also called Digital Twin. The entire factory can be seen as a set of CPSs and the resulting system is also called Cyber-Physical Production System (CPPS). This CPPS represents the Digital Twin of the factory with which it would be possible analyze the real factory. The interoperability between the real industrial equipment and the Digital Twin allows to make predictions concerning the quality of the products. More in details, these analyses are related to the variability of production quality, prediction of the maintenance cycle, the accurate estimation of energy consumption and other extra-functional properties of the system. Several tools [2] allow to model a production line, considering dierent aspects of the factory (i.e. geometrical properties, the information flows etc.) However, these simulators do not provide natively any solution for the design integration of CPSs, making impossible to have precise analysis concerning the real factory. Furthermore, for the best of our knowledge, there are no solution regarding a clear integration of data coming from real equipment into CPS models that composes the entire production line. In this context, the goal of this thesis aims to define an unified methodology to design and simulate the Digital Twin of a plant, integrating data coming from real equipment. In detail, the presented methodologies focus mainly on: integration of heterogeneous models in production line simulators; Integration of heterogeneous models with ad-hoc simulation strategies; Multi-level simulation approach of CPS and integration of real data coming from sensors into models. All the presented contributions produce an environment that allows to perform simulation of the plant based not only on synthetic data, but also on real data coming from equipments