Komponenttien luokittelu ja parhaat käytännöt tuotantosimulaation mallinnuksessa

Production simulation software plays a major role in validation, optimization and illustration of production systems. Operation of production simulation is generally based on components and their interaction. Components typically represent factory floor devices, but in addition, there can be components to provide visualization, statistics, control or other input to simulation. The demand for having high-quality, easy-to-use and compatible components emphasizes the importance of component modelling. The objectives of this thesis were to develop component classes based on industrial devices, to standardize component modelling solutions and best practices in component modelling. Other objectives were to identify and analyse future prospects of production simulation. This focuses on the concept of digital twin, which could be described as reflective real-time simulation model from the physical system. In addition, focus is also set on formal modelling languages. The outcome of this thesis presents component classes and best practices in component modelling. In component classification, the focus was set to development of generic components, which can be controlled with signal-based logic. This enables components from the software to be externally controlled. In addition, automatic model creation tool wizard, is implemented to instantly generate components based on the defined component classes. Best practices were based on the selected modelling fields that are most relevant for general use. In the development of best practices, interviewing method was utilized to receive input from simulation experts.Tuotantosimulaatio on tärkeässä osassa tuotantojärjestelmien validoinnissa, optimoinnissa ja visualisoinnissa. Tuotantosimulaation toiminta perustuu yleisesti komponentteihin ja niiden väliseen vuorovaikutukseen. Komponentit esittävät tyypillisesti tehtaasta löytyviä laitteita ja esineitä, mutta komponentteja voidaan käyttää myös visualisointiin, statistiikan keräämiseen, järjestelmän ohjaukseen tai muuhun tarpeeseen simuloinnissa. Tämän diplomityön tavoitteita oli kehittää komponenttiluokkia teollisuudesta valittujen laitteiden perusteella, mikä mahdollistaa mallinnusratkaisujen standardoinnin. Sen lisäksi tavoitteena oli kehittää parhaat käytännöt komponenttimallinnukseen. Muita tavoitteita oli tunnistaa ja analysoida tulevaisuuden näkymiä tuotantosimulaatiolle. Tämä keskittyi pääosin digitaaliseen kaksoseen, jota voidaan kuvata reaaliaikaisesti peilautuvaksi simulaatiomalliksi todellisesta järjestelmästä. Tämän lisäksi työssä keskityttiin formaaleihin mallinnuskieliin. Diplomityön lopputulos esittää kehitetyt komponenttiluokat ja parhaat käytännöt komponenttimallinnuksessa. Komponenttien luokittelussa keskityttiin kehittämään geneerisiä komponentteja, joita voidaan ohjata signaalipohjaisilla komennoilla. Tämä mahdollistaa komponentin ohjaamisen myös simulointiohjelman ulkopuolelta. Tämän lisäksi automaattista komponenttien luomistyökalua käytettiin luokiteltujen komponenttien luomisessa. Parhaat käytännöt komponenttimallinnuksessa pohjautuivat mallinnuksen oleellisimpiin osa-alueisiin tavanomaisissa mallinnustilanteissa. Parhaiden käytäntöjen kehityksessä haastateltiin simulointiammattilaisia, joiden mielipiteistä muodostettiin perusta käytäntöjen kehitykselle

Komponenttien luokittelu ja parhaat käytännöt tuotantosimulaation mallinnuksessa

Production simulation software plays a major role in validation, optimization and illustration of production systems. Operation of production simulation is generally based on components and their interaction. Components typically represent factory floor devices, but in addition, there can be components to provide visualization, statistics, control or other input to simulation. The demand for having high-quality, easy-to-use and compatible components emphasizes the importance of component modelling. The objectives of this thesis were to develop component classes based on industrial devices, to standardize component modelling solutions and best practices in component modelling. Other objectives were to identify and analyse future prospects of production simulation. This focuses on the concept of digital twin, which could be described as reflective real-time simulation model from the physical system. In addition, focus is also set on formal modelling languages. The outcome of this thesis presents component classes and best practices in component modelling. In component classification, the focus was set to development of generic components, which can be controlled with signal-based logic. This enables components from the software to be externally controlled. In addition, automatic model creation tool wizard, is implemented to instantly generate components based on the defined component classes. Best practices were based on the selected modelling fields that are most relevant for general use. In the development of best practices, interviewing method was utilized to receive input from simulation experts.Tuotantosimulaatio on tärkeässä osassa tuotantojärjestelmien validoinnissa, optimoinnissa ja visualisoinnissa. Tuotantosimulaation toiminta perustuu yleisesti komponentteihin ja niiden väliseen vuorovaikutukseen. Komponentit esittävät tyypillisesti tehtaasta löytyviä laitteita ja esineitä, mutta komponentteja voidaan käyttää myös visualisointiin, statistiikan keräämiseen, järjestelmän ohjaukseen tai muuhun tarpeeseen simuloinnissa. Tämän diplomityön tavoitteita oli kehittää komponenttiluokkia teollisuudesta valittujen laitteiden perusteella, mikä mahdollistaa mallinnusratkaisujen standardoinnin. Sen lisäksi tavoitteena oli kehittää parhaat käytännöt komponenttimallinnukseen. Muita tavoitteita oli tunnistaa ja analysoida tulevaisuuden näkymiä tuotantosimulaatiolle. Tämä keskittyi pääosin digitaaliseen kaksoseen, jota voidaan kuvata reaaliaikaisesti peilautuvaksi simulaatiomalliksi todellisesta järjestelmästä. Tämän lisäksi työssä keskityttiin formaaleihin mallinnuskieliin. Diplomityön lopputulos esittää kehitetyt komponenttiluokat ja parhaat käytännöt komponenttimallinnuksessa. Komponenttien luokittelussa keskityttiin kehittämään geneerisiä komponentteja, joita voidaan ohjata signaalipohjaisilla komennoilla. Tämä mahdollistaa komponentin ohjaamisen myös simulointiohjelman ulkopuolelta. Tämän lisäksi automaattista komponenttien luomistyökalua käytettiin luokiteltujen komponenttien luomisessa. Parhaat käytännöt komponenttimallinnuksessa pohjautuivat mallinnuksen oleellisimpiin osa-alueisiin tavanomaisissa mallinnustilanteissa. Parhaiden käytäntöjen kehityksessä haastateltiin simulointiammattilaisia, joiden mielipiteistä muodostettiin perusta käytäntöjen kehitykselle

Formal Digital Description of Production Equipment Modules for supporting System Design and Deployment

The requirements for production systems are moving towards higher flexibility, adaptability and reactivity. Increasing volatility in global and local economies, shorter product life cycles and the ever-increasing number of product variants arising from product customization have led to a demand for production systems which can respond more rapidly to these changing requirements. Therefore, whenever a new product, or product variant, enters production, the production system designer must be able to create an easily-reconfigurable production system which not only meets the User Requirements (UR) but is quick and cost-efficient to set up. Modern production systems must be able to integrate new product variants with minimum effort. In the event of a product changeover or an unforeseen incident, such as the mechanical failure of a production resource, it must be possible to reconfigure the production system smoothly and seamlessly by adding, removing or altering the resources. Ideally, auto-configuration should obviate the need to manually re-programme the system once it has been reconfigured.The cornerstone of any solution to the above-mentioned challenges is the concept of being able to create formalised, comprehensive descriptions of all production resources. Providing universally-recognised digital representations of all the multifarious resources used in a production system would enable a standardised exchange of information between the different actors involved in building a new production system. Such freely available and machine-readable information could also be utilised by the wide variety of software tools that come into play during the different life cycle phases of a production system, thus considerably extending its useful life. These digital descriptions would also offer a multi-faceted foundation for the reconfiguration of production systems. The production paradigms presented here would support state-of-the-art production systems, such as Reconfigurable Manufacturing Systems (RMSs), Holonic Manufacturing Systems (HMSs) and Evolvable Production Systems (EPSs).The methodological framework for this research is Design Research Methodology (DRM) supported with Systems Engineering, Action Research, and case-based research. The first two were used to develop the concept and data models for the resource descriptions, through a process of iterative development. The case-based research was used for verification, through the modelling and analysis of two separate production systems used in this research. The concept, on which this thesis is based, is itself based on the triplicity of production system design, i.e. Product, Process and Resource. The processes, are implemented through the capabilities of the resources, which are thus directly linked to the product requirements. The driving force behind this new approach to production system design is its strong emphasis on making production systems that can be reconfigured easily. Successful system reconfiguration can only be achieved, however, if all the required production resources can be quickly and easily compared to all the available production resources in one unified, and universally accepted form. These descriptions must not only be able to capture all of a production system’s capabilities, but must also include information about its interfaces, kinematics, technical properties and its control and communication abilities.The answer to this lies in the Emplacement Concept, which is described and developed in this thesis. The Emplacement Concept proposes the creation of a multi-layered Generic Model containing information about production resources in three different layers. These are the Abstract Module Description (AMD), the Module Description (MD), and the Module Instance Description (MID). Each of these layers has unique characteristics which can be utilised in the different phases of designing, commissioning and reconfiguring a production system. The AMD is the most abstract (general) descriptive layer and can be used for initial system design iterations. It ensures that the proposed resources for the production system are exchangeable and interchangeable, and thus guides the selection of production resources and the implementation (or reconfiguration) of a production system. The MD is the next level down, and provides a more detailed description of the type of production resource, providing ’finer granularity’ for the descriptions. The MID provides the finest level of granularity and contains invaluable information about the individual instances of a particular production resource. This research involves two practical implementations of the Generic Model. These are used to model and digitally represent all the production resources used in the two use-case environments. All the modules in the production systems (25 in all) were modelled and described with the data models developed here. In fact, we were able to freeze the data models after the first case study, as they didn’t need any major changes in order to model the production resources of the second use-case environment. This demonstrates the general applicability of the proposed approach for modelling modular production resources.The advantages of being able to describe production resources in a unified digital form are many and varied. For example, production systems which are described in this way are much more agile. They can react faster to changes in demand and can be reconfigured easily and quickly. The resource descriptions also improve the sustainability of production systems because they provide detailed information about the exact capabilities and characteristics of all the available resources. This means that production system designers are better placed to utilise ready-made modules, (design by re-use). Being able to use readily available production modules means that the Time to Market and Time to Volume are improved, as new production systems can be built or reconfigured using tested and fully operational modules, which can easily be integrated into an already operational production system. Finally, the resource descriptions are an essential source of information for auto-configuration tools, allowing automated, or semi-automated production system design. However, harvesting the full benefits of all these outcomes requires that the tools used to create new production systems can understand and utilise the modular descriptions proposed by this concept. This, in turn, presupposes that the all the formalised descriptions of the production modules provided here will be made publicly available, and will form the basis for an ever-expanding library of such descriptions

Ontology-Based Data Integration in Multi-Disciplinary Engineering Environments: A Review

Today's industrial production plants are complex mechatronic systems. In the course of the production plant lifecycle, engineers from a variety of disciplines (e.g., mechanics, electronics, automation) need to collaborate in multi-disciplinary settings that are characterized by heterogeneity in terminology, methods, and tools. This collaboration yields a variety of engineering artifacts that need to be linked and integrated, which on the technical level is reflected in the need to integrate heterogeneous data. Semantic Web technologies, in particular ontologybased data integration (OBDI), are promising to tackle this challenge that has attracted strong interest from the engineering research community. This interest has resulted in a growing body of literature that is dispersed across the Semantic Web and Automation System Engineering research communities and has not been systematically reviewed so far. We address this gap with a survey reflecting on OBDI applications in the context of Multi-Disciplinary Engineering Environment (MDEE). To this end, we analyze and compare 23 OBDI applications from both the Semantic Web and the Automation System Engineering research communities. Based on this analysis, we (i) categorize OBDI variants used in MDEE, (ii) identify key problem context characteristics, (iii) compare strengths and limitations of OBDI variants as a function of problem context, and (iv) provide recommendation guidelines for the selection of OBDI variants and technologies for OBDI in MDEE

Kommunikation und Bildverarbeitung in der Automation

In diesem Open Access-Tagungsband sind die besten Beiträge des 11. Jahreskolloquiums "Kommunikation in der Automation" (KommA 2020) und des 7. Jahreskolloquiums "Bildverarbeitung in der Automation" (BVAu 2020) enthalten. Die Kolloquien fanden am 28. und 29. Oktober 2020 statt und wurden erstmalig als digitale Webveranstaltung auf dem Innovation Campus Lemgo organisiert. 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 anschauliche Anwendungsbeispiele aus dem Bereich der Automation setzen die Ergebnisse in den direkten Anwendungsbezug

A framework for Model-Driven Engineering of resilient software-controlled systems

AbstractEmergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyber-physical systems to reliably provide services overcoming disruptions in operative conditions and adapting to changes in architectural and functional requirements. In this paper, we describe a hardware/software framework supporting operation and maintenance of software-controlled systems enhancing resilience by promoting a Model-Driven Engineering (MDE) process to automatically derive structural configurations and failure models from reliability artifacts. Specifically, a reflective architecture developed around digital twins enables representation and control of system Configuration Items properly derived from SysML Block Definition Diagrams, providing support for variation. Besides, a plurality of distributed analytic agents for qualitative evaluation over executable failure models empowers the system with runtime self-assessment and dynamic adaptation capabilities. We describe the framework architecture outlining roles and responsibilities in a System of Systems perspective, providing salient design traits about digital twins and data analytic agents for failure propagation modeling and analysis. We discuss a prototype implementation following the MDE approach, highlighting self-recovery and self-adaptation properties on a real cyber-physical system for vehicle access control to Limited Traffic Zones

Automatisierte, minimalinvasive Sicherheitsanalyse und Vorfallreaktion für industrielle Systeme

Automated defense and prevention measures designed to protect industrial automation and control systems often compromise their real-time processing, resilience and redundancy. Therefore, they need to be performed as non-invasively as possible. Nevertheless, particularly minimally invasive security analysis and incident response are still poorly researched. This work presents solutions based on new semantic- and SDN-based approaches to some of the most important problems in these areas

Automatisierte, minimalinvasive Sicherheitsanalyse und Vorfallreaktion für industrielle Systeme

Automated defense and prevention measures designed to protect industrial automation and control systems often compromise their real-time processing, resilience and redundancy. Therefore, they need to be performed as non-invasively as possible. Nevertheless, particularly minimally invasive security analysis and incident response are still poorly researched. This work presents solutions based on new semantic- and SDN-based approaches to some of the most important problems in these areas