Skip to main content

KI-Anwendungen im Kaizen-Management

  • Chapter
  • First Online:
Künstliche Intelligenz und schlanke Produktion

Zusammenfassung

Kaizen (oder Verbesserungs-) Aktivitäten sind der Kern der schlanken Produktion. Die folgenden verwandten Themen werden in diesem Kapitel besprochen:

  • Schlankheit, die das Ergebnis aller Kaizen-Aktivitäten ist.

  • 5S, einschließlich Kaizen-Aktivitäten zur Verbesserung der Arbeitsumgebung;

  • Vorausschauende Instandhaltung, einschließlich Kaizen-Aktivitäten zur Verbesserung der Zuverlässigkeit (oder Verfügbarkeit) von Geräten.

  • Reduzierung der Zykluszeit, die eine Hauptaufgabe bei der Verbesserung der Wertstromkarte (VSM) eines Produktionssystems ist.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Literatur

  1. S. Al Smadi, Kaizen strategy and the drive for competitiveness: challenges and opportunities. Compet. Rev. Int. Bus. J. 19(3), 203–211 (2009)

    Google Scholar 

  2. A. Susilawati, J. Tan, D. Bell, M. Sarwar, Fuzzy logic based method to measure degree of lean activity in manufacturing industry. J. Manuf. Syst. 34, 1–11 (2015)

    Article  Google Scholar 

  3. K.E.K. Vimal, S. Vinodh, Application of artificial neural network for fuzzy logic based leanness assessment. J. Manuf. Technol. Manag. 24(2), 274–292 (2013)

    Article  Google Scholar 

  4. E. Akyar, H. Akyar, S.A. Düzce, A new method for ranking triangular fuzzy numbers. Int. J. Uncertain. Fuzziness Knowl-Based Syst. 20(05), 729–740 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  5. M. Hanss, Applied Fuzzy Arithmetic (Springer-Verlag, 2005)

    Google Scholar 

  6. E. Van Broekhoven, B. De Baets, Fast and accurate center of gravity defuzzification of fuzzy system outputs defined on trapezoidal fuzzy partitions. Fuzzy Sets Syst. 157(7), 904–918 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  7. J. Michalska, D. Szewieczek, The 5S methodology as a tool for improving the organization. J. Achiev. Mater. Manuf. Eng. 24(2), 211–214 (2007)

    Google Scholar 

  8. J.S. Randhawa, I.S. Ahuja, An approach for justification of success 5S program in manufacturing organisations using fuzzy-based simulation model. Int. J. Prod. Qual. Manag. 25(3), 331–348 (2018)

    Google Scholar 

  9. S. Abbasbandy, T. Hajjari, A new approach for ranking of trapezoidal fuzzy numbers. Comput. Math. Appl. 57(3), 413–419 (2009)

    MathSciNet  MATH  Google Scholar 

  10. E. Pourjavad, R.V. Mayorga, A comparative study and measuring performance of manufacturing systems with Mamdani fuzzy inference system. J. Intell. Manuf. 30(3), 1085–1097 (2019)

    Article  Google Scholar 

  11. T. Allahviranloo, R. Saneifard, Defuzzification method for ranking fuzzy numbers based on center of gravity. Iran. J. Fuzzy Syst. 9(6), 57–67 (2012)

    MATH  Google Scholar 

  12. H. Shakouri, R. Nadimi, S.F. Ghaderi, Investigation on objective function and assessment rule in fuzzy regressions based on equality possibility, fuzzy union and intersection concepts. Comput. Ind. Eng. 110, 207–215 (2017)

    Article  Google Scholar 

  13. T. Chen, Y.C. Lin, A fuzzy-neural system incorporating unequally important expert opinions for semiconductor yield forecasting. Int. J. Uncertain. Fuzziness Knowl-Based Syst. 16(01), 35–58 (2008)

    Article  Google Scholar 

  14. H.C. Wu, T. Chen, C.H. Huang, A piecewise linear FGM approach for efficient and accurate FAHP analysis: smart backpack design as an example. Mathematics 8(8), 1319 (2020)

    Article  Google Scholar 

  15. T. Hafeez, L. Xu, G. Mcardle, Edge intelligence for data handling and predictive maintenance in IIOT. IEEE Access 9, 49355–49371 (2021)

    Article  Google Scholar 

  16. X. Chen, S. Jia, Y. Xiang, A review: knowledge reasoning over knowledge graph. Expert Syst. Appl. 141, 112948 (2020)

    Article  Google Scholar 

  17. C. Kahraman, D. Ruan, I. Doǧan, Fuzzy group decision-making for facility location selection. Inf. Sci. 157, 135–153 (2003)

    Article  MATH  Google Scholar 

  18. P.C. Chang, J.C. Hsieh, T.W. Liao, A case-based reasoning approach for due-date assignment in a wafer fabrication factory, in International Conference on Case-Based Reasoning (2001), pp. 648–659.

    Google Scholar 

  19. J.D. Little, OR FORUM—Little’s Law as viewed on its 50th anniversary. Oper. Res. 59(3), 536–549 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  20. M.L. Pinedo, Scheduling: Theory, Algorithms, and Systems (Springer, 2012)

    Google Scholar 

  21. S.C. Lu, D. Ramaswamy, P.R. Kumar, Efficient scheduling policies to reduce mean and variance of cycle-time in semiconductor manufacturing plants. IEEE Trans. Semicond. Manuf. 1(3), 374–385 (1998)

    Article  Google Scholar 

  22. T. Chen, Job remaining cycle time estimation with a post-classifying fuzzy-neural approach in a wafer fabrication plant: A simulation study. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 223(8), 1021–1031 (2009)

    Article  Google Scholar 

  23. A. Grigoriev, M. Uetz, Scheduling jobs with time-resource tradeoff via nonlinear programming. Discret. Optim. 6(4), 414–419 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  24. F. Pezzella, G. Morganti, G. Ciaschetti, A genetic algorithm for the flexible job-shop scheduling problem. Comput. Oper. Res. 35(10), 3202–3212 (2008)

    Article  MATH  Google Scholar 

  25. C. Blum, M. Sampels, An ant colony optimization algorithm for shop scheduling problems. J. Math. Model. Algorithms 3(3), 285–308 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  26. C.J. Liao, C.T. Tseng, P. Luarn, A discrete version of particle swarm optimization for flowshop scheduling problems. Comput. Oper. Res. 34(10), 3099–3111 (2007)

    Article  MATH  Google Scholar 

  27. X.A. Koufteros, Testing a model of pull production: a paradigm for manufacturing research using structural equation modeling. J. Oper. Manag. 17(4), 467–488 (1999)

    Article  Google Scholar 

  28. N. Watanabe, S. Hiraki, A mathematical programming model for a pull type ordering system including lot production processes. Int. J. Oper. Prod. Manag. 15(9), 44–58 (1995)

    Article  Google Scholar 

  29. F. Zhou, P. Ma, Y. He, S. Pratap, P. Yu, B. Yang, Lean production of ship-pipe parts based on lot-sizing optimization and PFB control strategy. Kybernetes 50(5), 1483–1505 (2020)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tin-Chih Toly Chen .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Der/die Autor(en), exklusiv lizenziert an Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Chen, TC.T., Wang, YC. (2023). KI-Anwendungen im Kaizen-Management. In: Künstliche Intelligenz und schlanke Produktion. Springer Vieweg, Cham. https://doi.org/10.1007/978-3-031-44280-3_3

Download citation

Publish with us

Policies and ethics