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Manufacturing-oriented enterprises are investing in novel solutions to adapt their cyber and physical resources to the fast and, yet, unexpected changes of global industrial environment. One of the important trends is to work towards development of cognitive systems which are capable to process and analyze complex data using Artificial Intelligence (AI)-based tools and techniques. Therefore, cognition can be already viewed as a requirement for hyper-connected environments e.g., the factories of the future or the Internet of Things (IoT). In this context, there is a need to represent and store the data collected from machines in a format that can be understood and manipulated by both humans and machines. This is feasible by designing and implementing semantic models i.e., ontologies which, in turn, enable inferring implicit data of explicit knowledge, leading to cognition. Moreover, there is a need of granting the access to such information remotely and at system runtime. Within this conceptual article, the authors present a semantic workbench that was developed during a European project aiming at utilization of ontologies for knowledge representation and reasoning in industrial automation systems. Further, this research work proposes the encapsulation of semantic workbench as a service in order to be deployed in cloud-based platforms, hence, enabling remote access of authorized clients at system runtime. The proposed functionalities are also of critical importance in highly complex and distributed environments, like the IoT or industrial ecosystems. acceptedVersion

Data collection requires homogenization of the data prior to processing it. This can create a challenge to the companies since data have varicose formats and schemas. This paper discusses the implementation of data collection framework using the PLANTCockpit open source platform, which is an integration platform for business processes. The framework is extended to fetch data from heterogeneous sources and then, allow the user to select the relevant data that matches his/her needs. In addition to this, the extendable framework also makes it possible to select the output data structure based on the user's requirements. Defining such a framework can reduce company's efforts for reshaping and modifying their architectures to handle new challenges posed by the ever-changing data. The framework not only restricts one to collection and transformation, but also provides an option to perform available processing techniques on the transformed data structure. The proposed framework has been tested on a cloud-based platform provided by the Cloud Collaborative Manufacturing Networks (C2NET) project. acceptedVersion

Industry 4.0 is about the interconnectivity and digitalisation of industrial systems that need to be integrated in order to improve the efficiency of resources and, in turn, processes. Both research and commercial sectors are working towards addressing specific challenges, such as data modelling, collection and processing. A correct manipulation and interpretation of data is critical and, now, more difficult than ever due to the dramatic increment of the amount of data generated at different levels of enterprises. Ultimately, this research work presents a solution, integrated with an existing cloud-based platform, for collecting and processing real-time factory shop floor streams of data. Such solution is an IoT-based development, which consist on both IoT hub and gateway that permit the consumption and communication of device information. The required message exchange is done within state of the art technologies and protocols e.g., MQTT protocol and REST-based interface. The implementation of the solution is demonstrated through an industrial-based scenario. acceptedVersion

Cyber-physical Systems (CPS) in industrial manufacturing facilities demand a continuous interaction with different and a large amount of distributed and networked computing nodes, devices and human operators. These systems are critical to ensure the quality of production and the safety of persons working at the shop floor level. Furthermore, this situation is similar in other domains, such as logistics that, in turn, are connected and affect the overall production efficiency. In this context, this article presents some key steps for integrating three pillars of CPS (production line, logistics and facilities) into the current smart manufacturing environments in order to adopt an industrial Cyber-Physical Systems of Systems (CPSoS) paradigm. The approach is focused on the integration in several digital functionalities in a cloud-based platform to allow a real time multiple devices interaction, data analytics/sharing and machine learning-based global reconfiguration to increase the management and optimization capabilities for increasing the quality of facility services, safety and energy efficiency and industrial productivity. Conceptually, isolated systems may enhance their capabilities by accessing to information of other systems. The approach introduces particular vision, main components, potential and challenges of the envisioned CPSoS. In addition, the description of one scenario for realizing the CPSoS vision is presented. The results herein presented will pave the way for the adoption of CPSoS that can be used as a pilot for further research on this emerging topic. acceptedVersion

Information technologies grow rapidly nowadays with the advance and extension of computing capabilities. This growth affects several fields, which consume these technologies. Industrial Automation is not an exception. This publication describes a general and flexible architecture for implementing Manufacturing Execution System (MES) function, which can be deployed in multiple industrial cases. These features are achieved by combining the flexibility of knowledge-driven systems with the vendor-independent property of RESTful web services. With deployment of this solution, MES functions may gain more versatility and independency. This research work is a continuation of the development of the OKD-MES (Open Knowledge-Driven Manufacturing Execution System) framework during the execution of the eScop project. The OKD-MES framework consists on a semantic-based solution for controlling and enhancing the flexibility and re-configurability of MES. In such scope, this research presents MES functions architecture that might be implemented in the OKD-MES framework in order to increase the flexibility of event-driven manufacturing systems. acceptedVersion

The advances in virtual engineering brought about the creation of models of physical systems. This has been enhanced by the use of relevant standards and web technologies to develop interfaces for monitoring and controlling industrial systems at the shop floor or remotely over the internet. However, owing to the open nature of the internet as well as vulnerabilities associated with internet-based technologies, it becomes imperative to put in place security measures. This will allow to mitigate this particularly as it concerns the management, control, and monitoring of entities making use of the interface. The first step is to ensure an efficient user access control for web-based solutions. This article proposes an approach for developing an access control layer to web applications. In addition, a web-based application, i.e., the FASTory simulator, is used as the test-bed for implementing this approach. acceptedVersion

Enterprise Resource Planning (ERP) represents the highest level of the manufacturing systems according to ISA-95 standard. It includes supply chain management, and customer-manufacturer-supplier interactions, essential to a successful business relationship in the frame of Industry 4.0. Many research efforts are being put in place to follows the latest ICT advances, combining them with manufacturing systems technologies. In this manner, the C2NET factories of future project (c2net-project.eu) has been put in place to provide a cloud-based collaborative network for supply chain interactions. This research paper focuses on providing a solution for retrieving ERP data via a Legacy System Hub, which is powered by the previous PlantCockpit project (www.tut.fi/plantcockpit-os/) outcomes. This solution allows the C2NET users to transfer the ERP data from the company side to the C2NET platform via the Data Collection Framework (DCF). Thus, the contribution of this research work is a generic solution that enables the interaction between systems owned by different organizations involved in the same supply chain. As C2NET targets the Small and Medium-sized Enterprises (SMEs), three data adapters are developed for MS Excel, SQL and RESTful data sources. The result of this research enhances the users experience in terms of interface and it might help in the C2NET databases for controlling and monitoring the instance changes in the ERP data on the company side. acceptedVersion

The industry is constantly moving towards the research, implementation and deployment of new solutions that permit the optimization of processes. Nowadays, such solutions consist mostly on ICT developments, which permit the collection, distribution, integration, analysis, and manipulation of heterogeneous data. The under way Cloud Collaborative Manufacturing Networks (C2NET) project targets the development of cloud-enabled tools for supporting the SMEs supply network optimization of manufacturing and logistic assets. The C2NET solution includes the implementation of paradigms as e.g. cloud computing or service-oriented and event-driven architectures, used for wide data integration. Among its requirements, the C2NET platform needs a solution for catch, process and react to events triggered in different locations of collaborative manufacturing networks, which are endowed with devices that permits the integration of Cyber-Physical Systems (CPS). This paper presents the architecture and main functionality of a knowledge-based approach that allows processing supply chain events handled by CPS devices. The main component of the presented solution is the SECA ontology, which is a knowledge base that can be updated at runtime. The main purpose of the ontology is to describe events, their status and the actions to be performed once a set of events are triggered in certain order. This research work offers a solution that can be employed by the C2NET platform not only to catch and process events; but also to notify linked data consumers. acceptedVersion

Virtualization has become a supportive approach for simulating system behaviour efficiently thanks to the revolution of computer and smart devices. In fact, the employment of running virtual tools that mimic the real physical world is nowadays a requirement in some fields as in e.g. industrial automation. This research work presents a virtual tool that simulates a real assembly line. The main features of this simulator are listed as; web application that can be accessed with any devices that supports html web pages, animated application that provides a UI for the user, discovery mechanism that allows web applications to interact with the simulator automatically and RESTful-based services, which increases the flexibility and versatility in terms of deployment. FASTory simulator has been developed and deployed during the eScop project. In addition, presented simulator has been employed by C2NET (Cloud Collaborative Manufacturing Networks) project for development some of its tools. Furthermore, the exploitation of the FASTory simulator is extended to cover as well the education of next generation of engineers for design and implementation of modern CPS. As Tampere University of Technology provides a M.Sc. degree in automation engineering, students use the simulator for their experiments, ensuring that mistakes are recoverable and harmless. acceptedVersion

Cyber-physical systems combine traditional data-processing systems with physical actuation capabilities. The physical aspect introduces new physical risks beyond the typical cyber risks related to information security. Cyber physical systems have an additional physical interface that must be protected from attacks. Furthermore, the physical actuation capabilities increase the potential amount of damage inflicted by a compromised system. The security risks are amplified when cloud computing is applied to provide the necessary data processing capabilities, since such task offloading increases the volume of network communication and the use of external computation resources. Network communication may be intercepted, inhibited, or manipulated. The use of external resources requires that the resource providers are trusted and maintain adequate information security levels. The security levels must be particularly strict, when critical planning and decision-making processes are offloaded on cloud resources. In such cases, poor selection of cloud service providers could compromise the operation of the entire system. This article first reviews recent research on security in cyber-physical systems. Finally, this article investigates methods to improve security in cloud-based cyber-physical systems by analyzing two application examples, a production system based on Service Oriented Architectures (SOA) and a smart-mobility system. Based on the analysis, this article investigates additional security measures to improve security in such systems. publishedVersion

Manufacturing execution systems play an important role of bridging high-level enterprise functions and production or manufacturing operations. The embedded systems are usually in charge of controlling execution of the operations. Modern embedded systems have become capable of simultaneous and deterministic execution of control algorithms and IP-based communication, making it possible to create complex cyber–physical systems (CPSs), where the computational and communication resources of a device can be used directly for various control, supervisory, or monitoring functions. The complexity for defining open-knowledge-driven manufacturing execution system (OKD-MES) is in maintaining awareness of overall system state to avoid disruptive actions as various functions may be requested from a system. The problem is that obtaining such information on system state may necessitate collecting data from a number of devices, as there may not be a single data point for state information. This paper describes and illustrates an approach for designing OKD-MES on top of CPSs that controls robot workstations and conveyor-based transportation system of a pallet-based production system. publishedVersion

Nowadays, street lighting accounts for 53% of outdoor lighting use, and the market is continuously increasing. In the context of rising energy prices and growing environmental awareness, energy efficiency is becoming one of the most important criteria for street lighting systems design. LED-based lights have become the primary option for replacing conventional light bulbs, being digitally controllable, small, highly efficient, and cheap to manufacture. Advanced control strategies adapted to ambient conditions are needed to combine low energy consumption and high-quality light ambience according to changing specifications. This paper describes an outdoor lighting solution aimed at energy-efficient performance in the context of multipurpose outdoor environments, where control is crucial in achieving efficiency improvements. This paper addresses efficiency at the component level, by optimizing the performance of LED drivers, and at the system level, by defining the control strategy and associated hardware infrastructure. The approach designed was tested in a real environment. The performance of the lighting installation was assessed using the Web-based monitoring application, providing real-time consumption information and aggregated historical data. This work was supported in part by the Spanish Government through the National Project “Estimation and Optimal Control for Energy Conversion with Digital Devices”, ECOTRENDD, under Grant TEC2014-52316-R, in part by ARTEMIS Joint Undertaking and the Finnish Funding Agency for Technology and Innovation through the ARTEMIS12 Project under Grant 332987.

In Europe, the manufacturing sector represents nearly the 22% of the GDP. Since the beginning of the European Technology Platform MANUFUTURE, Service Oriented Architecture have become the de facto in the industrial informatics research community. In most cases, SOA is implemented by using Web Service technology based on RESTful services or WS-* standards. Several publications have shown the advantages of WS technologies in Factory Automation e.g. enterprise integration, monitoring and control, real-time decision taking, maintenance scheduling, and reconfiguration. Monitoring has become an effortless task, leading to massive data to be processed in order to present a diagnostic i.e. asset-awareness. Further, once problems are identified, an automatic self-recovery mechanism should be provided in order to minimize loses. This paper introduce the eSONIA project which aims to improve the flow of information, rather than raw data, in the factory floor by enhancing the system awareness and granting self-recovery to the factory. To achieve this goal, eSONIA uses pervasive heterogeneous embedded devices intercommunicated with WS technologies over IPv6.

Human operators play an important role especially in high added value manufacturing. The use of knowledge representation for decision making at runtime becomes more important. Modern automatic control systems should be capable to seamlessly include and assist operators. This paper describes how to represent information on operator's skills and include it into service-oriented orchestration approach for a production line. This approach allows operator to act not as a passive element, but as active asset for the orchestration engine to consider in production plans. acceptedVersion