Top

Published in:

2023 | OriginalPaper | Chapter

3. KI-Anwendungen im Kaizen-Management

Authors : Tin-Chih Toly Chen, Yi-Chi Wang

Published in: Künstliche Intelligenz und schlanke Produktion

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

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.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Künstliche Intelligenz in der Fertigung

next chapter KI-Anwendungen in Pull-Produktion, JIT und Produktionsnivellierung

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

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)CrossRef

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)CrossRef

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)MathSciNetCrossRefMATH

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

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)MathSciNetCrossRefMATH

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

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)

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

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)CrossRef

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

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)CrossRef

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)CrossRef

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)CrossRef

15.

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

16.

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

17.

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

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.

19.

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

20.

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

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)CrossRef

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)CrossRef

23.

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

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)CrossRefMATH

25.

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

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)CrossRefMATH

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)CrossRef

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)CrossRef

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)CrossRef

Title: KI-Anwendungen im Kaizen-Management
Authors: Tin-Chih Toly Chen
Yi-Chi Wang
Publisher: Springer International Publishing
Book: Künstliche Intelligenz und schlanke Produktion
Print ISBN: 978-3-031-44279-7

Electronic ISBN: 978-3-031-44280-3

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-3-031-44280-3_3

Springer Professional

Zusammenfassung

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partners