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Intelligent product and mechatronic software components enabling mass customisation in advanced production systems

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Abstract

Up to the present time, the control software design of production systems has been developed to produce a certain number of goods, in a centralised manner and through a case-by-case, timely and costly process. Therefore, the current control design approaches hinder factories in their pursuit to acquire the essential capabilities needed in order to survive in this customer-driven and highly competitive market. Some of these vital production competencies include mass customisation, fault tolerance reconfigurability, handling complexity, scalability and agility. The intention of this research is to propose a uniform architecture for control software design of collaborative manufacturing systems. It introduces software components named as modular, intelligent, and real-time agents (MIRAs) that represent both intelligent products as clients (C-MIRA) and machines or robots as operators (O-MIRAs) in a production system. C-MIRAs are in constant interaction with customers and operators through human machine interfaces, and are responsible for transforming products from concepts up to full realisation of them with the least possible human intervention. This architecture is built upon the IEC 61499 standard which is recognised for facilitating the distributed control design of automation systems; however, it also takes into account the intelligent product concept and envisages the machines’ control to be composed of a set of modular software components with standardised interfaces. This approach makes the software components intuitive and easy to install, to create the desired behaviour for collaborative manufacturing systems and ultimately paves the way towards mass customisation. A simplified food production case study, whose control is synthesised using the proposed approach, is chosen as an illustrative example for the proposed methodology.

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References

  1. Vyatkin V et al (2006) Rapid engineering and re-configuration of automation objects aided by formal modelling and verification. Int J Manuf Res 1(4):382–404

    Article  Google Scholar 

  2. Koestler A (1969) The ghost in the machine. Arkana Books, London

    Google Scholar 

  3. Leitão P (2009) Holonic Rationale and self-organization on design of complex evolvable systems. In: Mařík V, Strasser T, Zoitl A (eds) Holonic and Multi-Agent Systems for Manufacturing. HoloMAS 2009. Lecture notes in computer science, vol 5696. Springer, Berlin, Heidelberg

  4. Hall KH, Staron RJ, Vrba P (2005) Experience with holonic and agent-based control systems and their adoption by industry. In: Mařík V, William Brennan R, Pěchouček M (eds) Holonic and Multi-Agent Systems for Manufacturing. HoloMAS 2005. Lecture Notes in Computer Science, vol 3593. Springer, Berlin, Heidelberg

  5. Bussmann S, Jennings NR, Wooldridge M (2004) Multiagent systems for manufacturing control: a design methodology. Springer, Berlin

    Book  Google Scholar 

  6. Merdan M, Lepuschitz W, Hegny I, Koppensteiner G (2009) Application of a communication interface between agents and the low level control. In: 4th. IEE International Conference on Autonomous Robots and Agents, Wellington, New Zealand, pp 628–633

  7. Lepuschitz W et al (2011) Toward self-reconfiguration of manufacturing systems using automation agents. IEEE Trans Syst Man Cybern Part C (Appl Rev) 41(1):52–69

    Article  Google Scholar 

  8. Li L, Yang Y (2008) Agent negotiation based ontology refinement process and mechanisms for service applications. SOCA 2(1):15–25

    Article  Google Scholar 

  9. Van Brussel H et al (1998) Reference architecture for holonic manufacturing systems: PROSA. Comput Ind 37(3):255–274

    Article  Google Scholar 

  10. Gouyon D, Pétin J-F, Morel G (2007) A product-driven reconfigurable control for shop floor systems. Studies in Informatics and Control, vol 16

  11. Simao JM, Tacla CA, Stadzisz PC (2009) Holonic control metamodel. IEEE Trans Syst Man Cybern Part A Syst Hum 39(5):1126–1139

    Article  Google Scholar 

  12. Covanich W et al. (2007) Integrating a new machine into an existing manufacturing system by using holonic approach. In: 2007 5th IEEE international conference on industrial informatics. IEEE

  13. McFarlane DC, Bussmann S (2000) Developments in holonic production planning and control. Prod Plan Control 11(6):522–536

    Article  Google Scholar 

  14. Shen W et al (2006) Applications of agent-based systems in intelligent manufacturing: an updated review. Adv Eng Inform 20(4):415–431

    Article  Google Scholar 

  15. Leitão P (2009) Agent-based distributed manufacturing control: a state-of-the-art survey. Eng Appl Artif Intell 22(7):979–991

    Article  MathSciNet  Google Scholar 

  16. Mathes M et al (2009) Time-constrained services: a framework for using real-time web services in industrial automation. SOCA 3(4):239

    Article  Google Scholar 

  17. Rapti E et al (2017) Decentralized service discovery and selection in Internet of Things applications based on artificial potential fields. SOCA 11(1):75–86

    Article  Google Scholar 

  18. Wang Z, Xu X (2012) A sharing-oriented service selection and scheduling approach for the optimization of resource utilization. SOCA 6(1):15–32

    Article  Google Scholar 

  19. Leitao P, Marik V, Vrba P (2012) Past, present, and future of industrial agent applications. IEEE Trans Ind Inform PP(99):1-1

    Google Scholar 

  20. Vyatkin V (2011) IEC 61499 as enabler of distributed and intelligent automation: state-of-the-art review. IEEE Trans Ind Inform 7(4):768–781

    Article  Google Scholar 

  21. Vyatkin V (2003) Intelligent mechatronic components: control system engineering using an open distributed architecture. In: Proceedings of IEEE conference on emerging technologies and factory automation, 2003. ETFA’03

  22. Pang C (2012) Model-driven development of distributed automation intelligence with IEC 61499. In: Electrical and computer engineering. The University of Auckland, p 125

  23. Zoitl A (2009) Real-time execution for IEC 61499. OSA & O3neida

  24. Sorouri M, Vyatkin V, Salcic Z (2014) MIRA: enabler of mass customization through agent-based development of intelligent manufacturing systems. In: IEEE international conference on robotics and automation (ICRA). Hong Kong

  25. Rachlin J et al (1999) A-teams: an agent architecture for optimization and decision-support. In: Müller J, Rao A, Singh M (eds) Intelligent agents V: agents theories, architectures, and languages. Springer, Berlin, pp 261–276

    Chapter  Google Scholar 

  26. Sorouri M et al (2015) Software composition and distributed operation scheduling in modular automated machines. IEEE Trans Ind Inform 11(4):865–878

    Article  Google Scholar 

  27. Lim MK, Zhang DZ (2004) An integrated agent-based approach for responsive control of manufacturing resources. Comput Ind Eng 46(2):221–232

    Article  Google Scholar 

  28. http://www.icreamfrisco.com/. Accessed Mar 2013

  29. nxtControl. (2014, 10/05). IDC Builder. Available: www.nxtcontrol.com

  30. Tichý P, Staron RJ (2010) Multi-agent technology for fault tolerant and flexible control. In: Srinivasan D, Jain LC (eds) Innovations in Multi-Agent Systems and Applications - 1. Studies in Computational Intelligence, vol 310. Springer, Berlin, Heidelberg

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Authors and Affiliations

  1. Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Majid Sorouri

  2. Luleå University of Technology, Luleå, Sweden

    Valeriy Vyatkin

  3. ITMO University, St. Petersburg, Russia

    Valeriy Vyatkin

  4. Aalto University, Helsinki, Finland

    Valeriy Vyatkin

Authors
  1. Majid Sorouri
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  2. Valeriy Vyatkin
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Correspondence to Majid Sorouri.

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Sorouri, M., Vyatkin, V. Intelligent product and mechatronic software components enabling mass customisation in advanced production systems. SOCA 12, 73–86 (2018). https://doi.org/10.1007/s11761-018-0230-8

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  • DOI: https://doi.org/10.1007/s11761-018-0230-8

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