A multiagent based knowledge extraction framework to support plug and produce capabilities in manufacturing monitoring systems

The manufacturing industry has been steadily evolving over the years, with new market trends encouraging manufacturers to find new ways to meet the consumers' demands and quickly adapt to new business opportunities. Manufacturing systems are therefore required to be more and more agile and flexible in an environment dominated by unpredictable changes and disturbances. As a direct consequence several new solutions have been proposed, revolving around agility, flexibility, reconfigurability and modularity, enabling concepts such as Plug & Produce (P&P). Following this trend, the present article proposes a possible implementation for a multiagent-based knowledge extraction architecture to support P&P in flexible, distributed manufacturing monitoring systems. The validation process is also described, entailing the application of said system in a real industrial environment, more specifically monitoring two robotic cells performing the welding of a car's side member.

[1]  Frank Vahid,et al.  A Survey on Concepts, Applications, and Challenges in Cyber-Physical Systems , 2014, KSII Trans. Internet Inf. Syst..

[2]  T. Kumpe,et al.  Manufacturing in the 1990s - productivity, flexibility and innovation , 1990 .

[3]  Mauro Onori,et al.  The IDEAS project: plug & produce at shop‐floor level , 2012 .

[4]  Svetan Ratchev,et al.  Towards a Capability-based Framework for Reconfiguring Industrial Production Systems , 2015 .

[5]  Lifeng Xi,et al.  A neural network ensemble-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes , 2009, Expert Syst. Appl..

[6]  José Barata,et al.  An agent based monitoring architecture for plug and produce based manufacturing systems , 2015, 2015 IEEE 13th International Conference on Industrial Informatics (INDIN).

[7]  Djamila Ouelhadj,et al.  Multi-agent architecture for distributed monitoring in flexible manufacturing systems (FMS) , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[8]  Hoda A. ElMaraghy,et al.  Flexible and reconfigurable manufacturing systems paradigms , 2005 .

[9]  Hosny A. Abbas.  Future SCADA challenges and the promising solution: the agent-based SCADA , 2014, Int. J. Crit. Infrastructures.

[10]  M. Onori,et al.  Evolvable Production Systems Context and Implications , 2007, 2007 IEEE International Symposium on Industrial Electronics.

[11]  Alois Zoitl,et al.  Monitoring and diagnostics of industrial systems using automation agents , 2011 .

[12]  Mauro Onori,et al.  Evolvable Production Systems: An Integrated View on Recent Developments , 2009, DET.

[13]  Xiaojun Zhou,et al.  Intelligent monitoring and diagnosis of manufacturing processes using an integrated approach of KBANN and GA , 2008, Comput. Ind..

[14]  Luis Ribeiro,et al.  Re-thinking diagnosis for future automation systems: An analysis of current diagnostic practices and their applicability in emerging IT based production paradigms , 2011, Comput. Ind..

[15]  Li Lin,et al.  Intelligent remote monitoring and diagnosis of manufacturing processes using an integrated approach of neural networks and rough sets , 2003, J. Intell. Manuf..

[16]  Yoram Koren,et al.  Design of reconfigurable manufacturing systems , 2010 .

[17]  Agostino Poggi,et al.  Developing Multi-agent Systems with JADE , 2007, ATAL.