Gonçalo Cândido

Evolvable production systems : An integrated view on recent developments

Evolvable Production Systems (EPS) is a fundamentally new paradigm to design, maintain and evolve industrial systems. It is a holistic approach supporting product/shop floor co-evolution and ensuring a tailored and balanced solution for sustainable enterprise development. Its core is engineered by distributed intelligence materialized in proactive and interacting shop floor assets. These intelligent building blocks include a wise interface design that ensures plug-ability and promotes system integration and bio-inspired interaction mechanisms (control and monitoring/diagnosis) to emerge a consistent self-organizing response to production disturbances. In this article a short survey on recent technical and theoretical developments supporting the EPS paradigm is held.

A Multiagent Based Control System Applied to an Educational Shop Floor

This paper addresses the design and implementation of a multiagent based control architecture to support modular reconfigurable production systems. The requirements for plugability of modules (manufacturing components) and product changes were considered and tested against an educational platform based of fischertechnik, which resembles a production system composed of several workstations connected by a crane and conveyors.

Towards a service based infrastructure to improve efficiency into energy systems: The NEMO&CODED quest

Energy efficiency is absolutely one of the greatest challenges of our days. The whole chain of actors involved in the generation, distribution, and consumption of energy are not only concerned but also acting towards a more rational and efficient use of energy. Additionally, the use of renewable energy sources also reflects the seriousness of the subject and helps to set up the current landscape on this matter. This is the rationale driving the NEMO&CODED (NEMO) project, which targets the development of a software infrastructure, based on web services and semantic resources aiming to provide the appropriate support to manage energy-related devices (e.g. renewable energy sources, smart meters, etc.) considering an environment where energy is generated, stored, distributed, and consumed in a rational and environmentally correct way. This shall be attained through the comprehensive implementation and instantiation of computational intelligence at resource level and the development of mechanisms that enable the seamless, and online, control/monitoring of aggregations of resources. This paper discusses the NEMO project, namely its vision, goals, preliminary software architecture, evaluation and assessment scenarios, and also points out the further work (research, design, and implementation) to be performed.

Self-Learning Production Systems: Adapter Reference Architecture

To face globalization challenges, today manufacturing companies require new and more integrated monitoring and control solutions in order to optimize more and more their production processes to enable a faster fault detection, reducing down-times during production, and improving system performances and throughput. Today industrial monitoring and control solutions give only a partial view of the production systems status, what compromises the accurate assessment of the system. In this scenario, integrating monitoring and control solutions for secondary processes into shop floor core systems guarantees a comprehensive overview on the entire system and its related processes since it provides access to a greater amount of information than before. The research currently done under the scope of Self-Learning Production Systems (SLPS) tries to fill this gap by providing a new and integrated way for developing monitoring and control solutions. This paper introduces the research background and describes the generic SLPS architecture and focus on the Adapter component responsible for adapting the system according to current context information. The proposed Adapter architecture and its core components are introduced as well as the generic Adaptation Process, i.e., its “modus operandi” to face context changes. Finally, one of three distinct business-case scenarios is presented to demonstrate the applicability of the envisioned reference architecture and Adapter solution into an industrial context as well as its behavior and adaptive ability along system lifecycle.

Adapter for Self-Learning Production Systems

To face globalization challenges, modern production companies need to integrate the monitoring and control of secondary processes into shop floor core system to remain competitive and improve system performance and throughput. The research currently being done under the scope of Self-Learning Production Systems tries to fill this gap. Current work introduces the domain and a generic architecture, while focus over the responsible element for executing system adaptations according to current context: the Adapter. The Adapter architecture and its components are introduced as well as the generic Adaptation process. Early prototype scenarios applied to concrete real-world scenarios are also presented.

Semantic SOA approach to support agile reengineering at device level

Abstract Recognized as the major deployed paradigm for business and enterprise integration, Service-oriented Architecture (SOA) is expanding into several domains of application, including production systems device level, envisioning a unified solution suitable across all different layers of an enterprise infrastructure. Additionally, semantic web research paves the way to allow machines to understand and process information. The merge of these two approaches promises to deliver more intelligent and automated systems able to understand the context and behave accordingly. The scope of this work mainly focuses on how to assist systems integrators during the discovery, identification and deployment of new devices in a service-oriented production system. To answer this need, this document presents and describes a semantic SOA approach, comprising a set of distributed components that can be employed in a combined manner to provide a complete range of services to enhance agility at device level during (re)engineering processes. This approach covers several different aspects of service-oriented production systems lifecycle, including the plug and unplug of new devices and services in a heterogeneous environment.

A MULTIAGENT BASED CONTROL SYSTEM FOR AN ASSEMBLY CELL

Abstract The main goal of this paper is to describe a multiagent based control architecture applied to a complex assembly cell in order to prove that the multiagent paradigm is a good alternative to develop agile control systems. By implementing the architecture we want to prove that it can be used for adequately solve requirements of: modularity, promote configuration rather than reprogramming, support various products simultaneously, and legacy controllers integration.