Semantic Driven Approach for Rapid Application Development in Industrial Internet of Things

The evolution of IoT has revolutionized industrial automation. Industrial devices at every level such as field devices, control devices, enterprise level devices etc., are connected to the Internet, where they can be accessed easily. It has significantly changed the way applications are developed on the industrial automation systems. It led to the paradigm shift where novel IoT application development tools such as Node-RED can be used to develop complex industrial applications as IoT orchestrations. However, in the current state, these applications are bound strictly to devices from specific vendors and ecosystems. They cannot be re-used with devices from other vendors and platforms, since the applications are not semantically interoperable. For this purpose, it is desirable to use platform-independent, vendor-neutral application templates for common automation tasks. However, in the current state in Node-RED such reusable and interoperable application templates cannot be developed. The interoperability problem at the data level can be addressed in IoT, using Semantic Web (SW) technologies. However, for an industrial engineer or an IoT application developer, SW technologies are not very easy to use. In order to enable efficient use of SW technologies to create interoperable IoT applications, novel IoT tools are required. For this purpose, in this paper we propose a novel semantic extension to the widely used Node-RED tool by introducing semantic definitions such as iot.schema.org semantic models into Node-RED. The tool guides a non-expert in semantic technologies such as a device vendor, a machine builder to configure the semantics of a device consistently. Moreover, it also enables an engineer, IoT application developer to design and develop semantically interoperable IoT applications with minimal effort. Our approach accelerates the application development process by introducing novel semantic application templates called Recipes in Node-RED. Using Recipes, complex application development tasks such as skill matching between Recipes and existing things can be automated.We will present the approach to perform automated skill matching on the Cloud or on the Edge of an automation system. We performed quantitative and qualitative evaluation of our approach to test the feasibility and scalability of the approach in real world scenarios. The results of the evaluation are presented and discussed in the paper.Die Entwicklung des Internet der Dinge (IoT) hat die industrielle Automatisierung revolutioniert. Industrielle Geräte auf allen Ebenen wie Feldgeräte, Steuergeräte, Geräte auf Unternehmensebene usw. sind mit dem Internet verbunden, wodurch problemlos auf sie zugegriffen werden kann. Es hat die Art und Weise, wie Anwendungen auf industriellen Automatisierungssystemen entwickelt werden, deutlich verändert. Es führte zum Paradigmenwechsel, wo neuartige IoT Anwendungsentwicklungstools, wie Node-RED, verwendet werden können, um komplexe industrielle Anwendungen als IoT-Orchestrierungen zu entwickeln. Aktuell sind diese Anwendungen jedoch ausschließlich an Geräte bestimmter Anbieter und Ökosysteme gebunden. Sie können nicht mit Geräten anderer Anbieter und Plattformen verbunden werden, da die Anwendungen nicht semantisch interoperabel sind. Daher ist es wünschenswert, plattformunabhängige, herstellerneutrale Anwendungsvorlagen für allgemeine Automatisierungsaufgaben zu verwenden. Im aktuellen Status von Node-RED können solche wiederverwendbaren und interoperablen Anwendungsvorlagen jedoch nicht entwickelt werden. Diese Interoperabilitätsprobleme auf Datenebene können im IoT mithilfe von Semantic Web (SW) -Technologien behoben werden. Für Ingenieure oder Entwickler von IoT-Anwendungen sind SW-Technologien nicht sehr einfach zu verwenden. Zur Erstellung interoperabler IoT-Anwendungen sind daher neuartige IoT-Tools erforderlich. Zu diesem Zweck schlagen wir eine neuartige semantische Erweiterung des weit verbreiteten Node-RED-Tools vor, indem wir semantische Definitionen wie iot.schema.org in die semantischen Modelle von NODE-Red einführen. Das Tool leitet einen Gerätehersteller oder Maschinebauer, die keine Experten in semantische Technologien sind, an um die Semantik eines Geräts konsistent zu konfigurieren. Darüber hinaus ermöglicht es auch einem Ingenieur oder IoT-Anwendungsentwickler, semantische, interoperable IoT-Anwendungen mit minimalem Aufwand zu entwerfen und entwicklen Unser Ansatz beschleunigt die Anwendungsentwicklungsprozesse durch Einführung neuartiger semantischer Anwendungsvorlagen namens Rezepte für Node-RED. Durch die Verwendung von Rezepten können komplexe Anwendungsentwicklungsaufgaben wie das Abgleichen von Funktionen zwischen Rezepten und vorhandenen Strukturen automatisiert werden. Wir demonstrieren Skill-Matching in der Cloud oder am Industrial Edge eines Automatisierungssystems. Wir haben dafür quantitative und qualitative Bewertung unseres Ansatzes durchgeführt, um die Machbarkeit und Skalierbarkeit des Ansatzes in realen Szenarien zu testen. Die Ergebnisse der Bewertung werden in dieser Arbeit vorgestellt und diskutiert

A knowledge based approach to integration of products, processes and reconfigurable automation resources

The success of next generation automotive companies will depend upon their ability to adapt to ever changing market trends thus becoming highly responsive. In the automotive sector, the assembly line design and reconfiguration is an especially critical and extremely complex job. The current research addresses some of the aspects of this activity under the umbrella of a larger ongoing research project called Business Driven Automation (BDA) project. The BDA project aims to carry out complete virtual 3D modeling-based verifications of the assembly line for new or revised products in contrast to the prevalent practice of manual evaluation of effects of product change on physical resources. [Continues.

SeLoC-ML: Semantic Low-Code Engineering for Machine Learning Applications in Industrial IoT

Internet of Things (IoT) is transforming the industry by bridging the gap between Information Technology (IT) and Operational Technology (OT). Machines are being integrated with connected sensors and managed by intelligent analytics applications, accelerating digital transformation and business operations. Bringing Machine Learning (ML) to industrial devices is an advancement aiming to promote the convergence of IT and OT. However, developing an ML application in industrial IoT (IIoT) presents various challenges, including hardware heterogeneity, non-standardized representations of ML models, device and ML model compatibility issues, and slow application development. Successful deployment in this area requires a deep understanding of hardware, algorithms, software tools, and applications. Therefore, this paper presents a framework called Semantic Low-Code Engineering for ML Applications (SeLoC-ML), built on a low-code platform to support the rapid development of ML applications in IIoT by leveraging Semantic Web technologies. SeLoC-ML enables non-experts to easily model, discover, reuse, and matchmake ML models and devices at scale. The project code can be automatically generated for deployment on hardware based on the matching results. Developers can benefit from semantic application templates, called recipes, to fast prototype end-user applications. The evaluations confirm an engineering effort reduction by a factor of at least three compared to traditional approaches on an industrial ML classification case study, showing the efficiency and usefulness of SeLoC-ML. We share the code and welcome any contributions.Comment: Accepted by the 21st International Semantic Web Conference (ISWC2022

Web service control of component-based agile manufacturing systems

Current global business competition has resulted in significant challenges for manufacturing and production sectors focused on shorter product lifecyc1es, more diverse and customized products as well as cost pressures from competitors and customers. To remain competitive, manufacturers, particularly in automotive industry, require the next generation of manufacturing paradigms supporting flexible and reconfigurable production systems that allow quick system changeovers for various types of products. In addition, closer integration of shop floor and business systems is required as indicated by the research efforts in investigating "Agile and Collaborative Manufacturing Systems" in supporting the production unit throughout the manufacturing lifecycles. The integration of a business enterprise with its shop-floor and lifecycle supply partners is currently only achieved through complex proprietary solutions due to differences in technology, particularly between automation and business systems. The situation is further complicated by the diverse types of automation control devices employed. Recently, the emerging technology of Service Oriented Architecture's (SOA's) and Web Services (WS) has been demonstrated and proved successful in linking business applications. The adoption of this Web Services approach at the automation level, that would enable a seamless integration of business enterprise and a shop-floor system, is an active research topic within the automotive domain. If successful, reconfigurable automation systems formed by a network of collaborative autonomous and open control platform in distributed, loosely coupled manufacturing environment can be realized through a unifying platform of WS interfaces for devices communication. The adoption of SOA- Web Services on embedded automation devices can be achieved employing Device Profile for Web Services (DPWS) protocols which encapsulate device control functionality as provided services (e.g. device I/O operation, device state notification, device discovery) and business application interfaces into physical control components of machining automation. This novel approach supports the possibility of integrating pervasive enterprise applications through unifying Web Services interfaces and neutral Simple Object Access Protocol (SOAP) message communication between control systems and business applications over standard Ethernet-Local Area Networks (LAN's). In addition, the re-configurability of the automation system is enhanced via the utilisation of Web Services throughout an automated control, build, installation, test, maintenance and reuse system lifecycle via device self-discovery provided by the DPWS protocol...cont'd

Simulation and Control of a Cyber-Physical System under IEC 61499 Standard

IEC 61499 standard provides an architecture for control systems using function blocks (FB), languages, and semantics. These devices can be interconnected and communicate with each other. Each device contains several resources and algorithms with a communication FB at the end, which can be created, configured, and deleted without affecting other resources. Physical element can be represented by a FB that encapsulates the functionality (data/events, process, return data/events) in a single module that can be reused and combined. This work presents a simplified implementation of a modular control system using a low-cost device. In the prototyping of the application, we use 4diac to control, model and validate the implementation of the system on a programmable logic controller. It is proved that this approach can be used to model and simulate a cyber-physical system as a single element or in a networked combination. The control models provide a reusable FB design.We acknowledge the financial support of CIDEM, R&D unit funded by FCT – Portuguese Foundation for the Development of Science and Technology, Ministry of Science, Technology and Higher Education, under the Project UID/EMS/0615/2019, and it was supported by FCT, through INEGI and LAETA, under project UIDB/50022/2020.info:eu-repo/semantics/publishedVersio

Successful Collaboration in Global Production Networks - fair, secured, connected

In today\u27s world, manufacturing companies face many challenges due to the uncertainty and complexity of environmental influences as well as increasing competitive pressures. The pandemic has clearly illustrated how volatile and fragile our supply chains have become. One way to overcome these chal-lenges together is to collaborate with other companies in the value network. Collaborations, i.e. successful cooperation with strategic partners and customers to achieve common goals, will continue to gain in importance. Instead of individual companies, entire value chains and networks will therefore compete with each other in the future. This will require a shift toward fast and seamless data exchange between the players in the value network. Advancing digitization and thus a generally increasingly networked world are increasingly supporting such collaborations, as the sharing and collaborative use of data is becom-ing much simpler. At the same time, the right handling of data will be decisive for competition. Digitization is moving from being a driver of change to an enabler of change. Innovative business models and the exploita-tion of the potential hidden in data will make it possible to realize reliable, flexible and, at the same time, resource-conserving value creation. The number of existing cloud-based collaboration platforms is growing steadily. Small and medium-sized enterprises in particular have to serve many different customer platforms at the same time, while they them-selves are still struggling with internal digitization challenges. Standardization initiatives for secure data rooms in the industry, such as GAIA-X, therefore hold great potential. In addition to these fundamental infrastructural issues, there are further challenges with regard to collaboration projects. Particular importance is attached to the competent handling of data protection and data security. There are often reservations that the disclosure of data and information will result in the loss of hard-earned expertise and com-petitive advantages that have been built up over time. At the same time, however, users from an engineering environment are only able to assess the risks of digital collaboration to a limited extent. In order to secure one\u27s own competitive position in the long term, digital competencies must therefore be built up and barriers to collaboration overcome. Success stories and clear recommendations for action can provide an important impetus for the implementation of successful collaboration projects, showing how collaborations can be approached in practice and what added value they generate. That is why we would like to provide manufacturing compa-nies with such guidance in the form of this action guide. The collaboration projects explained below and the best practices derived from them are intended to help companies find their own strategies on the path to more collaboration. We hope you enjoy reading this guide and are always available for questions and discussions

Ontology based semantic engineering framework and tool for reconfigurable automation systems integration

Digital factory modelling based on virtual design and simulation is now emerging as a part of mainstream engineering activities, and it is typically geared towards reducing the product design cycle time. Reconfigurable manufacturing systems can benefit from reusing the existing knowledge in order to decrease the required skills and design time to launch new product generations. The various industrial simulation systems are currently integrating product design, matching processes and resource requirements to decrease the required skills and design time to launch new products. However, the main focus of current reconfigurable manufacturing systems has been modular production lines to support different manufacturing tasks. Additionally, the design data is not transferrable from various domain-specific software to a collaborative and intelligent platform, which is required to capture and reuse design knowledge. Product design is still dependent on the knowledge of designers and does not link to the existing knowledge on processes and resources, which are in separate domains. To address these issues, this research developed an integration method based on semantic technologies and product, process, resource and requirements (PPRR) ontologies called semantic-ontology engineering framework (SOEF). SOEF transferred original databases to an ontology-based automation data structure with a semantic analysis engine. A pre-defined semantic model is developed to recognise custom requirement and map existing knowledge with processing data in the automation assembly aspect. The main research contribution is using semantic technology to process automation documentation and map semantic data to the PPRR ontology structure. Furthermore, this research also contributes to the automatic modification of system simulation based on custom requirements. The SOEF uses a JAVA-based command-line user interface to present semantic analysis results and import ontology outputs to the vueOne system simulation tool for system evaluation