Goncalo Candido

Service-Oriented Infrastructure to Support the Deployment of Evolvable Production Systems

Nowadays, Service-oriented Architecture (SOA) paradigm is becoming a broadly deployed standard for business and enterprise integration. It continuously spreads across the diverse layers of the enterprise organization and disparate domains of application envisioning a unified communication solution. In the industrial domain, Evolvable Production System (EPS) paradigm focus on the identification of guidelines and solutions to support the design, operation, maintenance, and evolution of complete industrial infrastructures. Similarly to several other domains, the crescent ubiquity of smart devices is raising important lifecycle concerns such as device setup, control, management, supervision and diagnosis. From initial setup and deployment to system lifecycle monitoring and evolution, each device needs to be taken into account and easily reachable. The present work exploits the association of EPS and SOA paradigms in the pursuit of a common architectural solution to support the different phases of the device lifecycle. The result is a modular, adaptive and open infrastructure forming a complete SOA ecosystem that will make use of the embedded capabilities supported by the proposed device model. The infrastructure components are specified and it is shown how they can interact and be combined to adapt to current system specificity and requirements. Finally, a proof-of-concept prototype deployed in a real industrial production scenario is also detailed and results are presented.

SOA at device level in the industrial domain: Assessment of OPC UA and DPWS specifications

Service-oriented Architecture (SOA) is increasingly relevant across several domains of application by promising systems openness and unification over a common design and communication paradigm. At device level, the application of SOA is carried, on one hand, by Devices Profile for Web Services (DPWS) and complementary web-based specifications oriented towards resource management, and, on the other hand, by OPC Unified Architecture (OPC UA) framework. These are currently the major candidates to be deployed at device level in a service-oriented industrial scenario. This document offers an overlook over both approaches, along with some complementary WS-* specifications through an extensive technical assessment. Also, it illustrates that neither one of these specifications can alone entirely cope with the requirements of service-oriented industrial domain device level and that a combined approach promises to deliver an important contribution. Synergies between the two sets of specifications for a more conformant solution are identified, and a convergence approach is enunciated in an era where it is imperative to avoid unnecessary layers of integration across enterprise infrastructure to ensure a more agile, lean and sustainable development.

DPWS as Specific Communication Service Mapping for IEC 61850

The present article describes the development of a standard-based software infrastructure, supported by the Service Oriented Architecture paradigm, for the management of complex distributed energy systems where efficient energy production, distribution and consumption are considered. The work has been developed on the context of the NEMO&CODED project (NEMO) and focuses on NEMOs architectural aim to enable seamless device integration, with plug and play features and vendor independent concepts, using the IEC 61850 ACSI model and services and adopting DPWS as Specific Communication Service Mapping.

IT support of mechatronic networks: A brief survey

The contribution of IT in reshaping the industrial automation contexts is undeniable. If years of investment in research have not been in vain, the next generation of automation devices shall be IT enabled. This research has been carried out in multidisciplinary teams fusing the Academia and Industry and has developed along two main lines: theoretical production paradigms and IT middleware support. This paper mainly concerns the second as it provides the instantiation mechanisms for the former. There is an ongoing dispute between Multiagent and Service Oriented concepts and platforms as implementation constructs. The literature is vast in detailing their application potential and inherent benefits. There is however a set of technical challenges that must be addressed if the next generation of IT-ready devices is to be properly exploited and the true value of emerging production paradigms extracted. In this context, the present paper reviews the main technical challenges matching them against a brief survey on recent research initiatives and supporting platforms.

A standard-based software infrastructure to support energy efficiency using renewable energy sources

The NEMO&CODED (NEMO) project targets the development of a standard-based software infrastructure, aiming to provide the appropriate support to manage energy-related devices considering an environment where energy is generated, stored, distributed, and consumed in a rational and environmentally correct way. This paper presents and discusses the results achieved so far by the project, with special emphasis on the implementation of a web services-based wrapper to seamlessly integrate new energy sources (renewable ones) into the NEMO network. Such a wrapper relies on the adoption of two standards, namely DPWS and the IEC 61850 series. The former handles service oriented related aspects whilst the latter helps to support the interoperability of Intelligent Electronic Devices (IEDs), through the use of the Abstract Communication Service Interface (ACSI) and the Substation Configuration Language (SCL). Main problems raised and solutions found are also included in the paper as well as the future steps to be performed.

Enhancing device exchange agility in Service-oriented industrial automation

The industrial automation domain is known for its plethora of heterogeneous equipment encompassing distinct functions, form factors, network interfaces and I/O specifications supported by dissimilar software and hardware platforms. There is then an evident and crescent need to take every device into account and improve the agility performance when handling device breakdowns or lifecycle modifications. Emerging from higher level IT domain, Service-oriented Architecture (SOA) paradigm is currently a widely endorsed approach for both business and enterprise systems integration. SOA promotes discoverability, loose coupling, abstraction, autonomy and composition of services relying on open web standards — features that can provide an important contribution to the industrial automation domain. The present work implements a SOA-based infrastructure comprising Semantic Web concepts to enhance the process of exchanging a device in an industrial automation environment by assisting (and even automate) this task supported by service and device semantic matching whenever a device breaks down or needs to be replaced. The infrastructure was implemented and tested in an educational shop floor setup composed by a set of distributed entities each one managed and controlled by its own SOA-ready PLC. The performed tests revealed that the tasks of discovering and identifying new devices, as well as providing assistance when a device is down or disconnected offered a valuable contribution and it can increase the agility of the overall system when dealing with operation disruptions or modifications at device level.

Service oriented computing to Self-Learning production system

The aim of this manuscript is to present what is Self-Learning production system and how service oriented architecture (SOA) and supporting technologies are bridged together to implement this new concept in the ongoing EU Self-Learning production system project. A brief review of the most recent EU projects that have reported results relevant to the main discussed investigation problems is presented. Reference architecture and functionalities of Self-Learning production system is introduced aiming for improved control and maintenance in production plants. Service oriented computing to Self-Learning production system is proposed to meet the required level of flexibility, interoperability and communications needs for reusable Self-Learning services. A roadmap for future research is defined.

Applications of Dynamic Deployment of Services in Industrial Automation

Service-oriented Architecture (SOA) is becoming a de facto paradigm for business and enterprise integration. SOA is expanding into several domains of application envisioning a unified solution suitable across all different layers of an enterprise infrastructure. The application of SOA based on open web standards can significantly enhance the interoperability and openness of those devices. By embedding a dynamical deployment service even into small field de- vices, it would be either possible to allow machine builders to place built- in services and still allow the integrator to deploy on-the-run the services that best fit his current application. This approach allows the developer to keep his own preferred development language, but still deliver a SOA- compliant application. A dynamic deployment service is envisaged as a fundamental framework to support more complex applications, reducing deployment delays, while increasing overall system agility. As use-case scenario, a dynamic deployment service was implemented over DPWS and WS-Management specifications allowing designing and programming an automation application using IEC61131 languages, and deploying these components as web services into devices.

Reliable Self-Learning Production Systems Based on Context Aware Services

The paper presents the key results of the EU-project Self-Learning. The strategic objective of Self-Learning is to strengthen EU leadership in production technologies in the global marketplace by developing innovative self-learning solutions to enable tight integration of control & so called secondary processes (e.g. maintenance, energy efficiency) of production systems. The project developed highly reliable and secure service-based self-learning solutions aiming at that integration. Approaches based on SOA principles, using distributed networked embedded services in device space, are the most appropriate for implementation of such self-learning solutions. Context awareness, providing information about the processes & equipment and circumstances under which the services operate and allowing them to react accordingly, is a promising holistic approach to assure needed self-learning adaptation to changes in processes and equipment states. The key components of a self-learning solution include a Context Extractor module to allow for dynamic context extraction, processing and storage, an Adapter module to allow for a holistic process control of considered systems and a self-learning module to allow for self-learning. Three industrial application scenarios drive the project.

Self-Learning approach to support lifecycle optimization of Manufacturing processes

Modern manufacturing companies are betting on the application of intelligent and more integrated monitoring and control solutions to reduce maintenance problems, production line downtimes and reduction of manufacturing operational costs while guarantying a more efficient management of the resources and an improved quality of products. The shoe industry provides a fertile ground in this direction since traditionally the production and manufacturing of shoes involves a wide variety of materials and a large number of both operations and machines characterized by a huge number of parameters as well. Thereby, the optimization of manufacturing process parameters during production activities is recognized as one of the most important task. As a matter of fact, the selection of the best set of manufacturing process parameters can improve final product quality, cost effectiveness while reducing anomalous situations that potentially may cause a line stopping. The present paper describes the research background that has driven the design and development of the Self-Learning methodology and reference architecture as the foundation for a new generation of monitoring and control solutions. Furthermore, a real application scenario from the shoe industry is also described to demonstrate the applicability of the proposed solution.