An AutomationML model for plug-and-produce assembly systems

This paper aims to support the creation of high performance ‘Plug-and-Produce’ systems by proposing a new semantic model that targets the use of AutomationML (AML). In this direction, the focus is narrowed to the self-description of equipment modules that highlights the use of ‘Skill’ concept. An insight description on how the concept of ‘Skill Recipe’ can be used to execute the equipment ‘Skills’ to fulfil the product's assembly requirements is also provided. This is viewed as a critical concept to achieve high performance in ‘Plug-and-Produce’. To translate the base semantic definitions, we have developed new libraries that are fully compliant with the AML standard. The main purpose of using AML in this context is to bridge production and other engineering domains. An overview of the literature that covers the past and current trends in data exchange and standards is presented, while pointing out the existing challenges and limitations. The vision of this paper is to support the standardization effort of integrating information for design, build, ramp-up and operation of production systems. Hence, this approach elucidates the use of existing AML concepts to model and instantiate Product, Process and Resource (PPR), and the underlying definitions such as: ‘Skills’, ‘Skill Recipes’ and ‘Skill Requirements’. Finally, this paper illustrates the implementation of this approach in AML with a help of an industrial case study demonstrated within the openMOS project

An event-based automationML model for the process execution of ‘plug-and-produce’ assembly systems

Assembly systems today are facing significant pressure to deliver high performance process executions, while being responsive to the fluctuating market demands. However, the implementation the trending Cyber Physical Systems concepts via ‘Plug-and-Produce’ devices produces some communication overheads. In this direction, the openMOS project aims to decouple the elements that are responsible for adaptation and general operations of the system. This allows the system to have two parallel processes. Towards this end, the priority is to deliver high performance process executions, while the other process focuses on delivering the required agility. The focus of this work is narrowed down to the development of task execution tables that guarantees high performance process executions. In this direction, the definition of task execution table is based on an existing AutomationML (AML) model that highlights the explicit relationships between the Product, Process and Resource (PPR) domains. A new decisional attribute has been added to the existing ‘Skill’ concept, which provides the flexibility to incorporate event-based process alternatives. An insight description on how the system handles process executions during run-time failures is also provided. Finally, this paper illustrates the run-time implementation of the execution table with a help of an industrial case study that has been used for a demonstration activity within the openMOS project

An event-based AutomationML model for the process execution of ‘Plug-and-Produce’ assembly systems

Assembly systems today are facing significant pressure to deliver high performance process executions, while being responsive to the fluctuating market demands. However, the implementation the trending Cyber Physical Systems concepts via ‘Plug-and-Produce’ devices produces some communication overheads. In this direction, the openMOS project aims to decouple the elements that are responsible for adaptation and general operations of the system. This allows the system to have two parallel processes. Towards this end, the priority is to deliver high performance process executions, while the other process focuses on delivering the required agility. The focus of this work is narrowed down to the development of task execution tables that guarantees high performance process executions. In this direction, the definition of task execution table is based on an existing AutomationML (AML) model that highlights the explicit relationships between the Product, Process and Resource (PPR) domains. A new decisional attribute has been added to the existing ‘Skill’ concept, which provides the flexibility to incorporate eventbased process alternatives. An insight description on how the system handles process executions during run-time failures is also provided. Finally, this paper illustrates the run-time implementation of the execution table with a help of an industrial case study that has been used for a demonstration activity within the openMOS projec

Realising the open virtual commissioning of modular automation systems

To address the challenges in the automotive industry posed by the need to rapidly manufacture more product variants, and the resultant need for more adaptable production systems, radical changes are now required in the way in which such systems are developed and implemented. In this context, two enabling approaches for achieving more agile manufacturing, namely modular automation systems and virtual commissioning, are briefly reviewed in this contribution. Ongoing research conducted at Loughborough University which aims to provide a modular approach to automation systems design coupled with a virtual engineering toolset for the (re)configuration of such manufacturing automation systems is reported. The problems faced in the virtual commissioning of modular automation systems are outlined. AutomationML - an emerging neutral data format which has potential to address integration problems is discussed. The paper proposes and illustrates a collaborative framework in which AutomationML is adopted for the data exchange and data representation of related models to enable efficient open virtual prototype construction and virtual commissioning of modular automation systems. A case study is provided to show how to create the data model based on AutomationML for describing a modular automation system

A Mapping Approach to Convert MTPs into a Capability and Skill Ontology

Being able to quickly integrate new equipment and functions into an existing plant is a major goal for both discrete and process manufacturing. But currently, these two industry domains use different approaches to achieve this goal. While the Module Type Package (MTP) is getting more and more adapted in practical applications of process manufacturing, so-called skill-based manufacturing approaches are favored in the context of discrete manufacturing. The two approaches are incompatible because their models feature different contents and they use different technologies. This contribution provides a comparison of the MTP with a skill-based approach as well as an automated mapping that can be used to transfer the contents of an MTP into a skill ontology. Through this mapping, an MTP can be semantically lifted in order to apply functions like querying or reasoning. Furthermore, machines that were previously described using two incompatible models can now be used in one production process

Selection of a data exchange format for industry 4.0 manufacturing systems

With the emergence of the Industry 4.0 concept, or the fourth industrial revolution, the industry is bearing witness to the appearance of more and more complex systems, often requiring the integration of various new heterogeneous, modular and intelligent elements with pre-existing legacy devices. This challenge of interoperability is one of the main concerns taken into account when designing such systems-of-systems, commonly requiring the use of standard interfaces to ensure this seamless integration. To aid in tackling this challenge, a common format for data exchange should be adopted. Thus, a study to select the foundations for the development of such a format is hereby presented, taking into account the specific needs of four different use cases representing varied key European industry sectors.info:eu-repo/semantics/publishedVersio

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

Model for web-application based configuration of modular production plants with automated PLC line control code generation

The international competition leads manufacturers in high-wage countries to focus more on high-value products, which often come at the disadvantage of small batch sizes. To remain competitive, the plant engineering for should be time and cost effective. One approach to achieve this are modular production lines. In the presented contribution, a product orientated web- service for the configuration of a modular production plant investigated. The resulting model then is interpreted by a code generator to generate a PLC line control. The approach is validated with a plant of metal hybrid carbon fiber seat rests

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