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About

José Barbosa has a PhD in Automation and Computer Science from the University of Valenciennes and Hainaut-Cambrésis (France) and a MSc in Industrial Engineering at IPB. He is a senior researcher at Polytechnic Institute of Bragança, Portugal, participating in several European funded projects, namely in the EU FP7 ARUM, in the EU FP7 GRACE project and in the EU H2020 PERFoRM and GO0DMAN. He is also an invited professor at the Department of Electrical Engineering of the Polytechnic Institute of Bragança. José Barbosa has more than 35 papers published at international journals and proceedings of international conferences. His main research topics focus on the development of self-organizing and evolvable manufacturing control architectures following the holonic and multi-agent system paradigms enriched with biological inspired mechanisms, particularly applied into Cyber-Physical Systems and Internet of Things. He is also a senior member of the IEEE and member of the IEEE Technical Committee on Industrial Agents.

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Publications

2018

Empowering a Cyber-Physical System for a Modular Conveyor System with Self-organization

Authors
Barbosa, J; Leitao, P; Teixeira, J;

Publication
Studies in Computational Intelligence

Abstract
The Industry 4.0 advent, advocating the digitalization and transformation of current production systems towards the factories of future, is introducing significant social and technological challenges. Cyber-physical systems (CPS) can be used to realize these Industry 4.0 compliant systems, integrating several emergent technologies, such as Internet of Things, big data, cloud computing and multi-agent systems. The paper analyses the advantages of using biological inspiration to empower CPS, and particularly those developed using distributed and intelligent paradigms such as multi-agent systems technology. For this purpose, the self-organization capability, as one of the main drivers in this industrial revolution is analysed, and the way to translate it to solve complex industrial engineering problems is discussed. Its applicability is illustrated by building a self-organized cyber-physical conveyor system composed by different individual modular and intelligent transfer modules. © 2018, Springer International Publishing AG.

2018

Multi-agent System Architecture for Zero Defect Multi-stage Manufacturing

Authors
Leitao, P; Barbosa, J; Geraldes, CAS; Coelho, JP;

Publication
SERVICE ORIENTATION IN HOLONIC AND MULTI-AGENT MANUFACTURING

Abstract
Multi-stage manufacturing, typical in important industrial sectors, is inherently a complex process. The application of the zero defect manufacturing (ZDM) philosophy, together with recent technological advances in cyber-physical systems (CPS), presents significant challenges and opportunities for the implementation of new methodologies towards the continuous system improvement. This paper introduces the main principles of a multi-agent CPS aiming the application of ZDM in multi-stage production systems, which is being developed under the EU H2020 GOOD MAN project. In particular, this paper describes the MAS architecture that allows the distributed data collection and the balancing of the data analysis for monitoring and adaptation among cloud and edge layers, to enable the earlier detection of process and product variability, and the generation of new optimized knowledge by correlating the aggregated data.

2018

Smart Inspection Tools Combining Multi-Agent Systems and Advanced Quality Control

Authors
Barbosa, J; Leitao, P; Ferreira, A; Queiroz, J; Angione, G; Lo Duca, G;

Publication
2018 IEEE 16TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)

Abstract
Although the everlasting goal of achieving a zero-defect production system is not new, the current state of the art has not yet allowed to reach this objective. This paper describes the architectural system foundations of the European R&D GO0DMAN project where a multi-agent system is developed as the mean to provide a real-time, multi-level and multi-stage approach to reach a zero-defect production system in multi-stage environments. Particularly, the paper focuses the integration of software agents and quality control stations forming smart inspection tools, aligned with the cyber-physical systems principles. The proposed approach is validated using an electrical motor testbed, where the agent-based system allows the digitization of the running testing system in a multi-stage schema.

2018

Reference Architecture for a Collaborative Predictive Platform for Smart Maintenance in Manufacturing

Authors
Balogh, Z; Gatial, E; Barbosa, J; Leitão, P; Matejka, T;

Publication
INES 2018 - IEEE 22nd International Conference on Intelligent Engineering Systems, Proceedings

Abstract
Maintenance is a key factor to ensure the production efficiency, since the occurrence of unexpected failures leads to a degradation of the system performance, causing the loss of productivity and business opportunities, which are crucial roles to achieve competitiveness. The article aims to propose a reference architecture which will improve the way maintenance is considered in the current manufacturing world, by enabling an overall increase of production rates, while increasing the operational equipment effectiveness and decreasing the impact of maintenance needs. This objective would be accomplished by establishing an IoT infrastructure for the collection of the huge amount of available shop floor data, which can be analyzed, considering data analytics algorithms, predictive maintenance models and forecasting techniques, to perform the machine/system health assessment and prediction of maintenance needs, e.g. by detecting earlier the occurrence of possible failures and consequently the need to implement maintenance interventions. The scheduling of predictive maintenance needs will be integrated with the existing maintenance planning tools, and especially synchronized with the production planning tools to achieve a nondisruptive maintenance impact in the production system. A cloud-based collaborative maintenance services platform allows the secure collection, aggregation and analysis of a large amount of shared data from numerous manufacturers that use the same or similar machinery, and acts as an open market where companies can contract specialized maintenance services. This reference architecture aims to provide replicable architecture to be broadly applicable in a variety of industries, capable to improve the production efficiency through a real-time health monitoring and early detection of failures and outages, to speed up the maintenance delivery, and consequently mitigate their impact. © 2018 IEEE.

2018

Performance assessment of the integration between industrial agents and low-level automation functions

Authors
Ribeiro, L; Karnouskos, S; Leitao, P; Barbosa, J; Hochwallner, M;

Publication
2018 IEEE 16TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)

Abstract
The increasing need for more adaptive production environments is a big motivator for the adoption of agent-based technologies in industrial systems, as they provide better mechanisms for handling dynamically and intelligently various kinds of production disturbances. Unlike with the utilization of most conventional automation languages, the use of agents enables, in an easy way, the setup of dynamic and autonomous adaptive processes to handle large and complex engineering system functions and interactions. Agent-technologies in cyber-physical systems contexts require at some point integration with automation controllers. However, most commonly available and used agent system implementations in the industry were not designed for hard real-time control use cases, and do not utilize real-time operating systems or dedicated hardware. Hence, they cannot match the hard-real-time performance of automation controllers. This work provides some insights on the performance that can be achieved with agent-based approaches that integrate with low-level automation system functions. It considers the performance of the agent-based practices in light of non-real-time dedicated hardware or operating systems. The results show that agents are well suited for the majority of soft-real-time control applications.