Jose Barata Oliveira

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.

Big Data Analysis to Ease Interconnectivity in Industry 4.0—A Smart Factory Perspective

Thriving and challenging market trends led to changes in the manufacturing industry. Production lines that need to adapt to customisable products on the fly emerged. By applying communication and sensors to the shop-floor, along with Industry 4.0 principles, this became a possibility. The growing amount of sensors led to an exponential boom of the amount of data available, creating the concept of Smart Factory. By applying Big Data Analysis to this data, it may be possible to optimise Smart Factories. There are technologies capable of doing this, even though only some are capable of guaranteeing Smart Factory requirements, such as real-time. A study of these technologies, based on SME’s experts’ opinion, is hereby presented to assess the most suitable ones to analyse Big Data in a Smart Factory environment.

A Highly Flexible, Distributed Data Analysis Framework for Industry 4.0 Manufacturing Systems

In modern manufacturing, high volumes of data are constantly being generated by the manufacturing processes. However, only a small percentage is actually used in a meaningful way. As part of the H2020 PERFoRM project, which follows the Industry 4.0 vision and targets the seamless reconfiguration of robots and machinery, this paper proposes a framework for the implementation of a highly flexible, pluggable and distributed data acquisition and analysis system, which can be used for both supporting run-time decision making and triggering self-adjustment methods, allowing corrections to be made before failures actually occur, therefore reducing the impact of such events in production.

Environment to Simulate Distributed Agent Based Manufacturing Systems

With the constant evolution of markets, new paradigms have emerged. Those new paradigms require solutions more versatile and able to cope with the unexpected changes. The world of manufacturing involves many risks and in order to reduce initial investments it is frequent to use virtual environments like simulators. This document presents a functional architecture of integration between a generic simulator and a multi-agent system, in order to meet the requirements of evolutions in manufacturing and the demand for customized products. One implementation case and results are presented as well.

Formal Specification of a Self-sustainable Holonic System for Smart Electrical Micro-grids

Stand-alone micro-grids have emerged within the smart grids field, facing important challenges related to their proper and efficient operation. An example is the self-sustainability when the micro-grid is disconnected from the main utility, e.g., due to a failure in the main utility or due to geographical situations, which requires the efficient control of energy demand and production. This paper describes the formal specification of a holonic system architecture that is able to perform the automation control functions in electrical stand-alone micro-grids, particularly aiming to improve their self-sustainability. The system aims at optimizing the power flow among the different electrical players, both producers and consumers, to keep the micro-grid operating even under adverse situations. The behaviour of each individual holon and their coordination patterns were modelled, analysed and validated using the Petri net formalism, allowing the complete verification of the system correctness during the design phase.

A Generic Reconfigurable and Pluggable Material Handling System Based on Genetic Algorithm

With the increasing customization of products there was a need to create new manufacturing systems that were able to satisfy these needs of the market. The Reconfigurable Manufacturing System (RMS) emerges as a more recent approach allowing the reconfiguration of the line and all the manufacturing systems. The balancing line is a common problem in the system reconfiguration but may not be enough, being also important to reconfigure the material handling system itself. Genetic Algorithms (GA) are one of the most known and used alternatives in optimization problems being widely used in shortest path problems like the travelling salesman. In this paper a solution that allows reconfiguring an agent based material handling system using a genetic algorithm is presented.

Digital Transformation in Service and Computing Oriented Manufacturing

This volume gathers the peer reviewed papers which were presented at the sixth edition of the International Workshop on “Service Orientation in Holonic and Multi-agent Manufacturing – SOHOMA’16” which was held on October 6–7, 2016 at the New University of Lisbon, Portugal. The book reports recent research in actual domains of the digital transformation in manufacturing and trends in future service and computing oriented manufacturing control.

Data Mining of Energy Consumption in Manufacturing Environment

Markets and consequently manufacturing companies are facing an unprecedented challenge. The constant markets demand of more and more customized and personalized products combined with the recent evolution of information technologies, brought to the manufacturing world the integration of new solutions previously unimaginable in a production environment. Hence, in the last years manufacturing systems were changing and nowadays each component present in the shop floor generates a huge amount of data that is usually not used. In this paper the authors present a framework capable to deal with all this data generated from a production cell in the automotive industry and reduce the energy consumption. Firstly, it is described how the information is extracted and how the data clustering is done, then the data mining process and management are presented, together with the obtained results.

An Evolvable and Adaptable Agent Based Smart Grid Management—A Simulation Environment

The liberalization of energy markets and shift towards intensive distributed use has provoked a change in the operating paradigm of electricity distribution networks. The continuity and the reliability of the distribution networks in the context of these new paradigms require structural and functional changes. The concept of Smart Grid allows the adaptation of distribution networks to the new context. This paper proposes an architecture organized to support the power transmission system, which auto management and control. The architecture is a multi-agent one, which uses the flow algorithm for a more efficient routing. Their main aim is stocking the entire electrical grid and distributing the energy effectively and efficiently between the various producers and consumers.

Semantic Model to Perform Pluggability of Heterogeneous Smart Devices into Smart City Environment

Nowadays smart cities are becoming more and more a hot topic in the technological world. Some different approaches emerged and many city departments approved investigation and implementation of the smart city technology in their cities. The implementation of these processes is becoming a landmark for the modern cities. This paper proposes a generic semantic model to easily plug and manage heterogeneous smart devices and areas of cities, in order to integrate all the diverse components that constitute a fully integrated and functional smart city environment. This semantic model can be used in the most diverse city scenarios; to demonstrate it, a specific scenario is presented in this paper, describing the usage of the proposed semantic model to detect new components and share information among the smart components.