Skip to main content

Abstract

In the framework of the SOHOMA 2020 special session “SOHOMA 10th-year anniversary”, this paper aims to make a review of the evolution of one important concept studied in the SOHOMA community, namely the Intelligent Product concept. This paper is not review of Intelligent Products - there are several of these already - but rather examines the history of the development of this concept through the 1st to 9th editions of SOHOMA, while also proposing future developments on this concept.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    www.scholar.google.fr / search: all in title: “intelligent products” OR “intelligent product”.

  2. 2.

    https://en.wikipedia.org/wiki/Co-occurrence_network.

  3. 3.

    Note that the complete list of references in *.bibtex/*.ris format as well as the VOSviewer files have been provided as supplementary material with the article submission.

  4. 4.

    PDS and ODS (Order-Driven Systems) are often used interchangeably.

  5. 5.

    These two citations are not extracted from SOHOMA proceedings.

  6. 6.

    https://www.aturnos.com/.

  7. 7.

    This citation is not issued from SOHOMA proceedings.

References

  1. Wong, C.Y., Mcfarlane, D., Zaharudin, A.A., Agarwal, V.: The intelligent product driven supply chain. In: Proceedings IEEE International Conference on Systems, Man and Cybernetics, pp. 4–6 (2002)

    Google Scholar 

  2. McFarlane, D., Sheffi, Y.: The impact of automatic identification on supply chain operations. Int. J. Logist. Manag. 14(1), 1–17 (2003)

    Article  Google Scholar 

  3. Kärkkäinen, M., Ala-Risku, T., Främling, K.: The product centric approach: a solution to supply network information management problems? Comput. Ind. 52(2), 147–159 (2003)

    Article  Google Scholar 

  4. Morel, G., Grabot, B.: Special issue on intelligent manufacturing. Eng. Appl. Artif. Intell. 16(4), 271–393 (2003)

    Article  Google Scholar 

  5. McFarlane, D., Giannikas, V., Wong, A.C.Y., Harrison, M.: Product intelligence in industrial control: Theory and practice. Annu. Rev. Control 37(1), 69–88 (2013)

    Article  Google Scholar 

  6. Meyer, G.G., Främling, K., Holmström, J.: Intelligent products: a survey. Comput. Ind. 60(3), 137–148 (2009)

    Article  Google Scholar 

  7. Srinivasan, R., McFarlane, D., Thorne, A.: Identifying the requirements for resilient production control systems. In: Studies in Computational Intelligence, vol. 640, pp. 125–134. Springer (2016)

    Google Scholar 

  8. Sallez, Y., Montreuil, B., Ballot, E.: On the activeness of physical internet containers. Stud. Comput. Intell. 594, 259–269 (2015)

    Google Scholar 

  9. Trentesaux, D., Thomas, A.: Product-driven control: a state of the art and future trends. IFAC Proc. 45(6), 716–721 (2012)

    Article  Google Scholar 

  10. Dubromelle, Y., Ounnar, F., Pujo, P.: Service oriented architecture for holonic isoarchic and multicriteria control. Stud. Comput. Intell. 402, 155–168 (2012)

    Google Scholar 

  11. Herrera, C., Berraf, S.B., Thomas, A.: Viable system model approach for holonic product driven manufacturing systems. Stud. Comput. Intell. 402, 169–181 (2012)

    Google Scholar 

  12. Adam, E., Trentesaux, D., Mandiau, R.: Volatile knowledge to improve the self-adaptation of autonomous shuttles in flexible job shop manufacturing system. Stud. Comput. Intell. 594, 219–231 (2015)

    Google Scholar 

  13. Mezgebe, T.T., El Haouzi, H.B., Demesure, G., Pannequin, R., Thomas, A.: A negotiation scenario using an agent-based modelling approach to deal with dynamic scheduling. Stud. Comput. Intell. 762, 381–391 (2018)

    Google Scholar 

  14. Zimmermann, E., El-Haouzi, H.B., Thomas, P., Pannequin, R., Noyel, M.: Using analytic hierarchical process for scheduling problems based on smart lots and their quality prediction capability. Stud. Comput. Intell. 803, 337–348 (2019)

    Google Scholar 

  15. Raileanu, S., Parlea, M., Borangiu, T., Stocklosa, O.: A JADE environment for product driven automation of holonic manufacturing. Stud. Comput. Intell.s 402, 265–277 (2012)

    Article  Google Scholar 

  16. Cardin, O., Castagna, P.: Myopia of service oriented manufacturing systems: benefits of data centralization with a discrete-event observer. In: Studies in Computational Intelligence (2012)

    Google Scholar 

  17. Cardin, O., Trentesaux, D., Thomas, A., Castagna, P., Berger, T., Bril, H.: Coupling predictive scheduling and reactive control in manufacturing: state of the art and future challenges. Stud. Comput. Intell. 594, 29–37 (2015)

    Google Scholar 

  18. Gaham, M., Bouzouia, B., Achour, N.: An evolutionary simulation-optimization approach to product-driven manufacturing control. In: Studies in Computational Intelligence, vol. 544, p. 283–294. Springer (2014)

    Google Scholar 

  19. Li, M., El Haouzi, H.B., Thomas, A., Guidat, A.: Fuzzy decision-making method for product holons encountered emergency breakdown in product-driven system: an industrial case. Stud. Comput. Intell. 594, 243–256 (2015)

    Google Scholar 

  20. Derigent, W., Voisin, A., Thomas, A., Kubler, S., Robert, J.: Application of measurement-based AHP to product-driven system control. Stud. Comput. Intell. 694, 249–258 (2017)

    Google Scholar 

  21. Aubry, A., Bril, H., Thomas, A., Jacomino, M.: Product driven systems facing unexpected perturbations: how operational research models and approaches can be useful? In: Studies in Computational Intelligence (2017)

    Google Scholar 

  22. Babiceanu, R.F., Seker, R.: Manufacturing operations, internet of things, and big data: towards predictive manufacturing systems. Stud. Comput. Intell. (2014)

    Google Scholar 

  23. Thomas, P., Thomas, A.: An approach to data mining for product-driven systems. In: Studies in Computational Intelligence, vol. 472, p. 181–194. Springer (2013)

    Google Scholar 

  24. Bouazza, W., Sallez, Y., Aissani, N., Beldjilali, B.: A model for manufacturing scheduling optimization through learning intelligent products. Stud. Comput. Intell. 594, 233–241 (2015)

    Google Scholar 

  25. Zimmermann, E., El Haouzi, H.B., Thomas, P., Pannequin, R., Noyel, M., Thomas, A.: A case study of intelligent manufacturing control based on multi-agents system to deal with batching and sequencing on rework context. In: Studies in Computational Intelligence (2018)

    Google Scholar 

  26. Queiroz, J., Leitão, P., Barbosa, J., Oliveira, E., Garcia, G.: An agent-based industrial cyber-physical system deployed in an automobile multi-stage production system. Stud. Comput. Intell. 853, 379–391 (2020)

    Google Scholar 

  27. McFarlane, D., Giannikas, V., Wong, A. C. Y., Harrison, M.: Intelligent products in the supply chain-10 years on, in Service orientation in holonic and multi agent manufacturing and robotics, p. 103–117. Springer (2013)

    Google Scholar 

  28. McFarlane, D., Sarma, S., Chirn, J.L., Wong, C.Y., Ashton, K.: Auto ID systems and intelligent manufacturing control. Eng. Appl. Artif. Intell. 16(4), 365–376 (2003)

    Article  Google Scholar 

  29. Derigent, W., Thomas, A.: situation awareness in product lifecycle information systems. Stud. Comput. Intell. 762, 127–136 (2018)

    Google Scholar 

  30. Cuthbert, R., Giannikas, V., McFarlane, D., Srinivasan, R.: Repair services for domestic appliances. Stud. Comput. Intell. 640, 31–39 (2016)

    Google Scholar 

  31. Derigen, W., Thomas, A.: End-of-life information sharing for a circular economy: existing literature and research opportunities. Stud. Comput. Intell. 640, 41–50 (2016)

    Google Scholar 

  32. Främling, K., Parmar, S., Hinkka, V., Tätilä, J., Rodgers, D.: Assessment of EPCIS standard for interoperable tracking in the supply chain. In: Studies in Computational Intelligence, vol. 472, pp. 119–134 (2013)

    Google Scholar 

  33. Ansola, P.G., García, A., de Las Morenas, J.: IoT visibility software architecture to provide smart workforce allocation. In: Studies in Computational Intelligence, vol. 640, pp. 223–231 (2016)

    Google Scholar 

  34. Kubler, S., Madhikermi, M., Främling, K.: QLM messaging standards: introduction and comparison with existing messaging protocols. In: Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics, vol. 544, pp. 237–256. Springer (2014)

    Google Scholar 

  35. Sallez, Y.: The augmentation concept: How to make a product “active” during its life cycle. Stud. Comput. Intell. 402, 35–48 (2012)

    Google Scholar 

  36. Sallez, Y.: Proposition of an analysis framework to describe the “activeness” of a product during its life cycle part ii: method and applications. In: Studies in Computational Intelligence, vol. 544, pp. 271–282. Springer (2014)

    Google Scholar 

  37. Basselot, V., Berger, T., Sallez, Y.: Active monitoring of a product: a way to solve the “lack of information” issue in the use phase. Stud. Comput. Intell. 694, 337–346 (2017)

    Google Scholar 

  38. Quintanilla, F.G., Cardin, O., Castagna, P.: Evolution of a flexible manufacturing system: from communicating to autonomous product. In: Studies in Computational Intelligence, vol. 472, pp. 167–180 (2013)

    Google Scholar 

  39. Kubler, S., Derigent, W., Thomas, A., Rondeau, É.: Key factors for information dissemination on communicating products and fixed databases. Service Orientation in Holonic and Multi-Agent Manufacturing Control, Paris 402, 89–102 (2012)

    Article  Google Scholar 

  40. Mekki, K., Derigent, W., Rondeau, E., Thomas, A.: Communicating aircraft structure for solving black-box loss on ocean crash. In: Studies in Computational Intelligence (2018)

    Google Scholar 

  41. Wan, H., David, M., Derigent, A.: Holonic manufacturing approach applied to communicate concrete: concept and first development. In: Studies in Computational Intelligence, Springer (2020)

    Google Scholar 

  42. Taboun, M.S., Brennan, R.W.: Sink node embedded, multi-agent systems based cluster management in industrial wireless sensor networks. Stud. Comput. Intell. 640, 329–338 (2016)

    Google Scholar 

  43. Trentesaux, D., Branger, G.: Data management architectures for the improvement of the availability and maintainability of a fleet of complex transportation systems: a state-of-the-art review. Stud. Comput. Intell. 762, 93–110 (2018)

    Google Scholar 

  44. Trentesaux, D., Branger, G.: Foundation of the surfer data management architecture and its application to train transportation, international workshop on service orientation in holonic and multi-agent manufacturing. Stud. Comput. Intell. 762, 111–125 (2018)

    Google Scholar 

  45. Morariu, O., Morariu, C., Borangiu, T.: Resource, service and product: real-time monitoring solution for service oriented holonic manufacturing systems. Stud. Comput. Intell. 544, 47–62 (2014)

    Google Scholar 

  46. Tsamis, N., Giannikas, V., McFarlane, D., Lu, W., Strachan, J.: Adaptive storage location assignment for warehouses using intelligent products. Stud. Comput. Intell. 594, 271–279 (2015)

    Google Scholar 

  47. Cojocaru, L.E., Burlacu, G., Popescu, D., Stanescu, A.M.: Farm management information system as ontological level in a digital business ecosystem. In: Studies in Computational Intelligence, vol. 544, pp. 295–309. Springer (2014)

    Google Scholar 

  48. Răileanu, S., Borangiu, T., Silişteanu, A.: Centralized HMES with environment adaptation for production of radiopharmaceuticals. Stud. Comput. Intell. 640, 3–20 (2016)

    Google Scholar 

  49. Pǎtraşcu, M., Drǎgoicea, M.: Integrating agents and services for control and monitoring: managing emergencies in smart buildings. Stud. Comput. Intell. 544, 209–224 (2014)

    Google Scholar 

  50. Thomson, V., Zhang, X.: Improving the delivery of a building. Stud. Comput. Intell. 640, 21–29 (2016)

    Google Scholar 

  51. Montreuil, B.: Toward a physical internet: meeting the global logistics sustainability grand challenge. Logist. Res. 3(2), 71–87 (2011)

    Article  Google Scholar 

  52. Ballot, E., Gobet, O., Montreuil, B.: Physical internet enabled open hub network design for distributed networked operations. Stud. Comput. Intell. 402, 279–292 (2012)

    Google Scholar 

  53. Rahimi, A., Sallez, Y., Berger, T.: Framework for smart containers in the physical interne. In: Studies in Computational Intelligence, vol. 640, pp. 71–79. Springer (2016)

    Google Scholar 

  54. Krommenacker, N., Charpentier, P., Berger, T., Sallez, Y.: On the usage of wireless sensor networks to facilitate composition/decomposition of physical internet containers. In: Studies in Computational Intelligence, vol. 640, pp. 81–90. Springer (2016)

    Google Scholar 

  55. Pujo, P., Ounnar, F., Remous, T.: Wireless holons network for intralogistics service. Stud. Comput. Intell. 594, 115–124 (2015)

    Google Scholar 

  56. Pujo, P., Ounnar, F.: Cyber-physical logistics system for physical internet. In: Studies in Computational Intelligence, vol. 762, pp. 303–316 (2018)

    Google Scholar 

  57. Glaessgen, E., Stargel, D.: The digital twin paradigm for future NASA and US Air Force vehicles. In: 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, p. 1818 (2012)

    Google Scholar 

  58. Valckenaers, P.: ARTI reference architecture - PROSA revisited. Stud. Comput. Intell. 803, 1–9 (2019)

    Google Scholar 

  59. Borangiu, T., Oltean, E., Răileanu, S., Anton, F., Anton, S., Iacob, I.: Embedded digital twin for ARTI-type control of semi-continuous production processes. Stud. Comput. Intell. 853, 113–133 (2020)

    Google Scholar 

  60. Lu, Q., Xie, X., Heaton, J., Parlikad, A.K., Schooling, J.: From BIM towards digital twin: strategy and future development for smart asset management. Stud. Comput. Intell. 853, 392–404 (2020)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to William Derigent .

Editor information

Editors and Affiliations

Appendix

Appendix

See Table 1

Table 1. List of references extracted from SOHOMA Proceedings, ranked by cluster and year

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Derigent, W., McFarlane, D., Bril El-Haouzi, H. (2021). Intelligent Products through SOHOMA Prism. In: Borangiu, T., Trentesaux, D., Leitão, P., Cardin, O., Lamouri, S. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2020. Studies in Computational Intelligence, vol 952. Springer, Cham. https://doi.org/10.1007/978-3-030-69373-2_26

Download citation

Publish with us

Policies and ethics