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Superior Performance of Leagile Supply Networks by Application of Autonomous Control

  • Bernd Scholz-Reiter
  • Afshin Mehrsai
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 338)

Abstract

In the paper, a special approach to supply networks’ material flows is posed. The considered strategy is based on the both principles of Lean and agility, beside push and pull of materials. Here, the trade off between positioning of decoupling point throughout an exemplary network, and reduction of inventory level along throughput time is examined. Moreover, autonomous control for material routing and lot-sizes is taken into account. To do so, a discrete-event simulation model is developed to show the performances.

Keywords

Leagile Production Network Autonomous Control Dynamic 

References

  1. 1.
    Whicker, L., Bernon, M., Templar, S., Mena, C.: Understanding the relationships between time and cost to improve supply chain performance. Int. J. Production Economics (2006), doi:10.1016/j.ijpe.2006.06.022Google Scholar
  2. 2.
    Tu, Q., Vonderembse, M.A., Ragu-Nathan, T.S.: The impact of time-based manufacturing practices on mass customization and value to customer. J. of Operation Management 19(2), 201–217 (2001)CrossRefGoogle Scholar
  3. 3.
    Fredriksson, P., Gadde, L.E.: Flexibility and rigidity in customization and built-to-order production. Industrial Marketing Management 34(7), 695–705 (2005)CrossRefGoogle Scholar
  4. 4.
    Romano, P.: Co-ordination and integration mechanisms to manage logistics processes across supply networks. J. of Purchasing & Supply Management 9, 119–134 (2003)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Scholz-Reiter, B., Jagalski, T., de Beer, C., Freitag, M.: Autonomous Shop Floor Control Considering Set-up Time. In: Proc. of 40th CIRP International Seminar on Manufacturing Systems, Liverpool, UK, pp. 1–6 (2007)Google Scholar
  6. 6.
    Li, S., Ragu-Nathan, B., Ragu-Nathan, T.S., Subba Rao, S.: The impact of supply chain management practices on competitive advantage and organizational performance. J. of Management Science, Omega 34, 107–124 (2006)CrossRefGoogle Scholar
  7. 7.
    Mason-Jones, R., Towill, D.R.: Using the Information Decoupling Point to Improve Supply Chain Performance. Int. J. of Logistics Management 10(2), 13–26 (1999)CrossRefGoogle Scholar
  8. 8.
    Sun, X.Y., Ji, P., Sun, L.Y., Wang, Y.L.: Positioning multiple decoupling points in a supply network. Int. J. Production Economics 113, 943–956 (2008)CrossRefGoogle Scholar
  9. 9.
    Hoek, R.I.V.: The thesis of leagility revisited. Int. J. of Agile Management Systems 2(3), 196–201 (2000)CrossRefGoogle Scholar
  10. 10.
    Wanddhwa, S., Mishra, M., Saxena, A.: A network approach for modeling and design of agile supply chains using a flexibility construct. Int. J. of Felxible Manufacturing System 19(4), 410–442 (2007)CrossRefGoogle Scholar
  11. 11.
    Yusuf, Y.Y., Gunasekaran, A., Adeleye, E.O., Sivayoganathan, K.: Agile supply chain capabilities: Determination of competitive objectives. European J. of Operational Research 159, 379–392 (2004)zbMATHCrossRefGoogle Scholar
  12. 12.
    Lau Antonio, K.W., Yam, R.C.M., Tang, E.: The impact of product modularity on competitive capabilities and performance: An empirical study. Int. J. Production Economics 105, 1–20 (2007)CrossRefGoogle Scholar
  13. 13.
    Ernst, R., Kamrad, B.: Evaluation of supply chain structures through modularized and postponement. European J. of Operation Research 124, 495–510 (2000)zbMATHCrossRefGoogle Scholar
  14. 14.
    Avneet, S., Wadhwa, S.: Flexible configuration for seamless supply chains: Directions towards decision knowledge sharing. Robotics and Computer-Integrated Manufacturing 25, 839–852 (2009)CrossRefGoogle Scholar
  15. 15.
    Scholz-Reiter, B., Jagalski, T., Bendul, J.C.: Autonomous control of a shop floor based on bee’s foraging behavior. In: Kreowski, H.J., Scholz-Reiter, B., Haasis, H.D. (eds.) Dynamics in Logistics. First Int. Conf., LDIC 2007, pp. 415–423. Springer, Heidelberg (2007)Google Scholar
  16. 16.
    Vogel, A., Fischer, M., Jaehn, H., Teich, T.: Real-world shop floor scheduling by ant colony optimization. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) ANTS 2002. LNCS, vol. 2463, pp. 268–273. Springer, Heidelberg (2002)Google Scholar
  17. 17.
    Scholz-Reiter, B., Wirth, F., Freitag, M., Dashkovskiy, S., Jagaslki, T., de Beer, C., Rüffer, B.: Some remarks on the stability of manufacturing logistic networks. Stability margins. In: Proc. of the Int. Scientific Annu. Conf. on Operations Research, pp. 91–96. Springer, Bremen (2006)Google Scholar
  18. 18.
    Scholz-Reiter, B., de Beer, C., Freitag, M., Jagalski, T.: Bio-inspired and pheromone-based shop-floor control. Int. J. Computer Integrated Manufacturing 21(2), 201–205 (2008)CrossRefGoogle Scholar
  19. 19.
    Nythuis, P., Wiendahl, H.P.: Logistic Production Operating Curves- Basic Model of the Theory of Logistic Operating Curves. CIRP Annals- Manufacturing Technology 55, 441–444 (2006)CrossRefGoogle Scholar
  20. 20.
    Scholz-Reiter, B., Mehrsai, A., Goerges, M.: Handling the Dynamics in Logistics- Adoption of Dynamic Behavior and Reduction of Dynamic Effects. Asian Int. J. of Science and Technology (AIJSTPME) 2(3), 99–110 (2009)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2010

Authors and Affiliations

  • Bernd Scholz-Reiter
    • 1
  • Afshin Mehrsai
    • 1
  1. 1. BremenGermany

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