The Influence of Manufacturing System Characteristics on the Emergence of Logistics Synchronization: A Simulation Study

  • Stanislav M. ChankovEmail author
  • Giovanni Malloy
  • Julia Bendul
Conference paper
Part of the Lecture Notes in Logistics book series (LNLO)


The term “synchronization” in manufacturing refers to the provision of the right components to the subsequent production steps at the right moment in time. It is still unclear how manufacturing system characteristics impact synchronization. Thus, the purpose of this paper is to investigate the effect of manufacturing systems’ characteristics on the emergence of logistics synchronization in them. We conduct a discrete-event simulation study to examine the effect of three system characteristics: (1) material flow network architecture, (2) work content variation, and (3) order arrival pattern. Our findings suggest that the material flow network architecture and the work content variation are related to logistics synchronization. Linear manufacturing systems with stable processing times such as flow shops operate at high logistics synchronization levels, while highly connected systems with high variability of processing times such as job shops exhibit lower synchronization levels.


Synchronization Manufacturing system Discrete-event simulation 


  1. Becker C, Scholl A (2006) A survey on problems and methods in generalized assembly line balancing. Eur J Oper Res 168(3):694–715MathSciNetCrossRefzbMATHGoogle Scholar
  2. Becker T et al (2012) The impact of network connectivity on performance in production logistic networks. CIRP J Manuf Sci Technol 5(4):309–318CrossRefGoogle Scholar
  3. Becker T, Chankov SM, Windt K (2013) Synchronization measures in job shop manufacturing environments. Procedia CIRP 7:157–162CrossRefGoogle Scholar
  4. Bondi A, Whitt W (1986) The influence of service-time variability in a closed network of queues. Perform Eval 6(3):219–234MathSciNetCrossRefGoogle Scholar
  5. Chankov SM, Becker T, Windt K (2014) Towards definition of synchronization in logistics systems. Procedia CIRP 17:594–599CrossRefGoogle Scholar
  6. Chankov SM, Huett M-T, Bendul J (2015) Synchronization in manufacturing systems: quantification and relation to logistics performance. Submitted to International Journal of Production ResearchGoogle Scholar
  7. Chryssolouris G (2006) Manufacturing systems: theory and practice, 2nd ed. Springer, New YorkGoogle Scholar
  8. Erdős P, Rényi A (1959) On random graphs I. Publ. Math. Debrecen 6:290–297MathSciNetzbMATHGoogle Scholar
  9. Field A (2013) Discovering statistics using ibm spss statistics, 4th edn. SAGE Publications, LondonGoogle Scholar
  10. Freiheit T, Shpitalni M, Hu SJ (2004) Productivity of paced parallel-serial manufacturing lines with and without crossover. J Manuf Sci Eng 126(2):361CrossRefGoogle Scholar
  11. Fretter C et al (2010) Phase synchronization in railway timetables. Eur Phys J B 77(2):281–289CrossRefGoogle Scholar
  12. Kelton WD, Law AM (2000) Simulation modeling and analysis. McGraw Hill, BostonzbMATHGoogle Scholar
  13. Miller WA, Davis RP (1989) Synchronization of material flow to aid production planning in a job shop. Eng Manage Int 5(3):179–184CrossRefGoogle Scholar
  14. Mood AMF, Graybill FA, Boes DC (1974) Introduction to the theory of statistics, 3rd edn. McGraw-Hill, New YorkzbMATHGoogle Scholar
  15. Pikovsky A, Rosenblum M, Kurths J (2003) Synchronization: a universal concept in nonlinear sciences. Cambridge University Press, CambridgezbMATHGoogle Scholar
  16. Wiendahl H-H (1998) Zentralistische Planung in dezentralen Strukturen?—Orientierungshilfen für die Praxis. In: Westkämper E, Schraft RD (eds) Auftrags- und Informationsmanagement in Produktionsnetzwerken—Konzepte und Erfahrungsberichte. Fraunhofer IPA, Stuttgart, pp 79–107Google Scholar
  17. Witte J De (1980) The use of similarity coefficients in production flow analysis. Int J Prod Res 18(4):503–514CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Stanislav M. Chankov
    • 1
    Email author
  • Giovanni Malloy
    • 2
  • Julia Bendul
    • 1
  1. 1.Department of Mathematics and LogisticsJacobs University BremenBremenGermany
  2. 2.School of Industrial Engineering, Purdue UniversityWest LafayetteUSA

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