IJAT Vol.9 No.3 pp. 270-282
doi: 10.20965/ijat.2015.p0270


Towards Decentralized Production: A Novel Method to Identify Flexibility Potentials in Production Sequences Based on Flexibility Graphs

Lennart Bochmann*1,*2, Lars Gehrke*1,*3, Adrian Böckenkamp*4, Frank Weichert*4, Rainer Albersmann*5, Christian Prasse*6, Christoph Mertens*6, Marco Motta*6, and Konrad Wegener*2

*1Volkswagen AG
Berliner Ring 2, 38440 Wolfsburg, Germany

*2Institute of Machine Tools and Manufacturing, ETH Zurich, Zurich, Switzerland

*3Chair of Enterprise Logistics, Technical University of Dortmund, Dortmund, Germany

*4Department of Computer Science VII, Technical University of Dortmund, Dortmund, Germany

*5F/L/S Fuzzy Logik Systeme GmbH, Dortmund, Germany

*6Fraunhofer Institute for Material Flow and Logistics, Dortmund, Germany

December 19, 2014
April 13, 2015
May 5, 2015
decentralized production, flexibility potentials, modeling of flexibility graphs, volume cycle, Industry 4.0

Due to higher degrees of individualization, shorter product life cycles, and volatile selling markets, fulfilling customer demands — the main task of automotive companies — has become very complex. In order to tackle this complexity, new concepts that enable the decentralization of decision-making within the production process have become promising solutions. The advancement towards self-organized production requires novel approaches in the field of production program planning. This work introduces the concept of the volume cycle as a new design factor in program planning. Additionally, a novel method to identify flexibility potentials in production sequences based on ,flexibility graphs is proposed, and the method is validated through a case study considering a segment of the assembly process for an automobile. Suitable visualization techniques for flexibility graphs are also discussed. Furthermore, in order to allow automatic analysis and evaluation of the flexibility potentials, methods of graph mining are introduced and the application possibilities of these techniques in terms of analyzing flexibility graphs are clarified. The results obtained from the case study illustrate that routing flexibility is not leveraged in today’s production lines, thus revealing a potential optimization domain.

Cite this article as:
L. Bochmann, L. Gehrke, A. Böckenkamp, F. Weichert, R. Albersmann, C. Prasse, C. Mertens, M. Motta, and K. Wegener, “Towards Decentralized Production: A Novel Method to Identify Flexibility Potentials in Production Sequences Based on Flexibility Graphs,” Int. J. Automation Technol., Vol.9, No.3, pp. 270-282, 2015.
Data files:
  1. [1]  D. Archambault, T. Munzner, and D. Auber, “TopoLayout: Multilevel Graph Layout by Topological Features,” IEEE Transactions on Visualization and Computer Graphics, Vol.13, No.2, pp. 305–317, March, 2007.
  2. [2]  J. Aurich, “Automobilproduktion,” Springer Vieweg, 2014.
  3. [3]  R. F. Aziz, “RPERT: Repititive-Projects Evaluation and Review Technique,” Alexandria Engineering Journal, Vol.53, pp. 81–93, 2013.
  4. [4]  K. Baker, “Introduction to Sequencing and Scheduling,” Wiley, New York, 1974.
  5. [5]  G. Battista, P. Eades, R. Tamassia, and I. Tollis, “Graph Drawing: Algorithms for the Visualization of Graphs,” Prentice Hall PTR, Upper Saddle River, NJ, USA, 1st edition, 1998.
  6. [6]  T. Bauernhansl, M. ten Hompel, and B. Vogel-Heuser (Eds.), “Industrie 4.0 in Produktion, Automatisierung und Logistik,” Springer Vieweg, Wiesbaden, 2014.
  7. [7]  J. Blazewicz and D. Kobler, “Review of properties of different precedence graphs for scheduling problems,” European Journal of Operational Research, Vol.142, pp. 435–443, 2002.
  8. [8]  K. Brauer, F. Zesch, M. Motta, C. Schwede, A. Wagenitz, C. Reeker, K. Liebler, J. Maass, C. Engmann, S. Schneider, P. Thomas, M. Preuss, J. Kemper, A. Hermes, M. Marr, and M. Florian, “Integrierte Terminierung und Transportplanung füur komplexe Wertschöopfungsstrukturen: Partnerbericht zum Projektabschluss: Fraunhofer-Institut Materialfluss und Logistik,” Technical report, Fraunhofer Institute for Material Flow and Logistics, Berlin, 2011.
  9. [9]  J. Browne, D. Dubois, K. Rathmill, S. P. Sethi, and K. E. Stecke, “Classification of flexible manufacturing systems,” Flexible Manufacturing Systems Magazine, Vol.2, pp. 114–117, 1984.
  10. [10]  M. Broy, H. Fischer, K. Beetz, and W. Damm, “Cyber-Physical Systems,” Springer, 2010.
  11. [11]  J. Buzacott, “Production Planning and Control: Basics and Concepts,” Oldenbourg, Müunchen, 2012.
  12. [12]  Capgemini Consulting, “Industry 4.0 – The Capgemini Consulting View,” Website, 2014, sites/default/files/resource/pdf%/capgemini-consulting-industrie-4.0_0.pdf [accessed December 15, 2014]
  13. [13]  D. Chakrabarti and C. Faloutsos, “Graph Mining: Laws, Tools, and Case Studies,” Synthesis Lectures on Data Mining and Knowledge Discovery, Morgan & Claypool Publishers, 2012.
  14. [14]  M. Chimani, C. Gutwenger, M. Jüunger, G. Klau, K. Klein, and P. Mutzel, “The Open Graph Drawing Framework (OGDF),” In R. Tamassia, editor, Handbook of Graph Drawing and Visualization, chapter 17, pp. 543–569, CRC Press, 2013.
  15. [15]  W. D. Cottrell, “Simplified Program Evaluation and Review Technique (PERT),” Journal of Construction Engineering and Management, 1999.
  16. [16]  M. Dijk, R. Orsato, and R. Kemp, “The emergence of an electric mobility trajectory,” Energy Policy, Vol.52, pp. 135–145, 2013, Special Section: Transition Pathways to a Low Carbon Economy.
  17. [17]  E. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik, Vol.1, No.1, pp. 269–271, 1959.
  18. [18]  H. ElMaraghy, “Flexible and reconfigurable manufacturing systems paradigms,” International Journal of Flexible Manufacturing Systems, Vol.17, No.4, pp. 261–276, October, 2006.
  19. [19]  European Factories of the Future Research Association, “Multi Annual Roadmap for the Contractual PPP under Horizon 2020,” 2013.
  20. [20]  R. Floyd, “Algorithm 97: Shortest Path,” Communications of the ACM, Vol.5, No.6, p. 345, June, 1962.
  21. [21]  German Government, “Hightech Strategie Industrie 4.0,” [accessed December 9, 2014]
  22. [22]  O. Goldreich, S. Goldwasser, and D. Ron, “Property testing and its connection to learning and approximation,” In Proceedings of the 37th Annual Symposium on Foundations of Computer Science, pp. 339–348, October 1996.
  23. [23]  B. Grafen, “Prozessorientierte Auftragsabwicklung in der Automobilindustrie,” Ph.D. thesis, Philipps-Universit”at Marburg, 2001.
  24. [24]  W. Güunthner and M. ten Hompel (Eds.), “Internet der Dinge in der Intralogistik,” Springer, Berlin, 2010.
  25. [25]  T. Gupta, “Applying the Critical Path Method to Manufacturing Routing,” Computers industrial Engineering, Vol.21, Nos.1–4, pp. 519 – 523, 1991.
  26. [26]  P. Hart, N. Nilsson, and B. Raphael, “A Formal Basis for the Heuristic Determination of Minimum Cost Paths,” IEEE Transactions on Systems Science and Cybernetics, Vol.4, No.2, pp. 100–107, July, 1968.
  27. [27]  W. Herlyn, “PPS im Automobilbau: Produktionsprogrammplanung und steuerung von Fahrzeugen und Aggregaten,” Fahrzeugtechnik, Hanser Verlag, Müunchen, 2012.
  28. [28]  A. Hermes, “Modellbasierte Bewertung von Potenzialen einer distributionsorientierten Programm- und Reihenfolgeplanung in der Automobilindustrie,” Verlag Praxiswissen, Dortmund, 2011.
  29. [29]  T. Jéeron and C. Jard, “3D Layout of Reachability Graphs of Communicating Processes,” In Proceedings of the DIMACS International Workshop on Graph Drawing, GD ’94, pp. 25–32, Springer-Verlag, London, UK, 1995.
  30. [30]  H. Kagermann, W. Wahlster, and J. Helbig, “Recommendations for implementing the strategic initiative Industrie 4.0,” Technical report, acatech, 2013.
  31. [31]  A. Kahn, “Topological Sorting of Large Networks,” Communications of the ACM, Vol.5, No.11, pp. 558–562, November, 1962.
  32. [32]  K.-C. Kim, C. Sohn, T. Roemer, and A. Yassine, “Configuration and Coordination of Activities within a Supply Chain,” International Journal of Automation Technology, Vol.6, No.1, pp. 6–19, 2006.
  33. [33]  F. Klug, “Logistikmanagement in der Automobilindustrie: Grundlagen der Logistik im Automobilbau,” Springer-Verlag, Heidelberg, 2010.
  34. [34]  Y. Koren, U. Heisel, F. Jovane, T. Moriwaki, G. Pritschow, G. Ulsoy, and H. Van Brussel, “Reconfigurable Manufacturing Systems,” Annals of the CIRP, Vol.48, No.2, pp. 527–540, 1999.
  35. [35]  Y. Koren and M. Shpitalni, “Design of reconfigurable manufacturing systems,” Journal of Manufacturing Systems, Vol.29, pp. 130–141, 2010.
  36. [36]  A. Lester, “Project Management, Planning and Control,” Vol.5, Butterworth Heinemann, 2007.
  37. [37]  H. Li, F. Karray, O. Basir, and I. Song, “Multi-Agent Based Control of a Heterogeneous System,” Journal of Advanced Conputational Intelligence and Intelligent Informatics, Vol.10, No.2, pp. 161–167, 2006.
  38. [38]  . Lu and H. Li, “Resource-Activity Critical-Path Method for Construction Planning,” Journal of Construction Engineering and Management, 2003.
  39. [39]  E. Martins, “On a multicriteria shortest path problem,” European Journal of Operational Research, Vol.16, No.2, pp. 236–245, May, 1984.
  40. [40]  H. B. Maynard, G. J. Stegemerten, and J. L. Schwab, “Methods-Time Measurement,” McGraw-Hill Book Company Inc., New York, 1948.
  41. [41]  M. G. Mehrabi, Y. Ulsoy, and G. Koren, “Reconfigurable manufacturing systems: Key to future manufacturing,” Journal of Intelligent Manufacturing, Vol.11, pp. 403–419, 2000.
  42. [42]  L. Monostori, J. Váancza, and S. Kumara, “Agent-based systems for manufacturing,” CIRP Annals-Manufacturing Technology, Vol.55, No.2, pp. 697–720, 2006.
  43. [43]  X. Niu, H. Ding, and Y. Xiong, “A hierarchical approach to generating precedence graphs for assembly planning,” International Journal of Machine Tools & Manufacture, Vol.43, No.14, pp. 1473–1486, 2003.
  44. [44]  Plattform Industrie 4.0, [accessed December 9, 2014]
  45. [45]  T. O. Prenting and R. M. Battaglin, “The precedence diagram: A tool for analysis in assembly line balancing.,” Journal of Industrial Engineering, Vol.15, No.4, pp. 208–213, 1964.
  46. [46]  P. Schoensleben, “Changeability of strategic and tactical production concepts,” CIRP Annals – Manufacturing Technology, Vol.58, No.1, pp. 383–386, 2009.
  47. [47]  G. Schuh and V. Stich, “Produktionsplanung und steuerung 1: Grundlagen der PPS,” Vol.4, Springer Berlin Heidelberg, Berlin and Heidelberg, 2012.
  48. [48]  G. Schuh, N. Wemhöoner, and C. Friedrich, “Scenario-based Lifecycle Analysis of Manufacturing Systems,” CIRP – Journal of Manufacturing Systems, Vol.35, No.2, 2006.
  49. [49]  R. Sedgewick, “Algorithms,” Addison-Wesley, Upper Saddle River, NJ, 2011.
  50. [50]  A. Sethi and S. Sethi, “Flexibility in Manufacturing: A Survey,” The International Journal of Flexibility Manufacturing Systems, Vol.2, pp. 289–328, 1990.
  51. [51]  M. Sugi, M. Cheng, M. Yamamoto, H. Ito, K. Inoue, and J. Ota, “System Rescheduling in Seminconductor Manufacturing,” International Journal of Automation Technology, Vol.4, No.2, pp. 184–197, 2010.
  52. [52]  K. Sugiyama, S. Tagawa, and M. Toda, “Methods for Visual Understanding of Hierarchical System Structures,” IEEE Transactions on Systems, Man and Cybernetics, Vol.11, No.2, pp. 109–125, February, 1981.
  53. [53]  R. Tamassia, “Handbook of Graph Drawing and Visualization (Discrete Mathematics and Its Applications),” Chapman & Hall/CRC, 2007.
  54. [54]  M. Vanhoucke, “Project Management with Dynamic Scheduling,” Spirnger Berling Heidelberg, 2012.
  55. [55]  A. Wagenitz, “Modellierungsmethode zur Auftragsabwicklung in der Automobilindustrie,” PhD thesis, TU Dortmund, 2007.
  56. [56]  G. Weigert, T. Heinlich, and A. Klemmt, “Methods for Modelling and Optimisation of Assembly Processes,” Advances in Simulation for Production and Logistics Applications, 2008.
  57. [57]  A. Zubaryeva, C. Thiel, E. Barbone, and A. Mercier, “Assessing factors for the identification of potential lead markets for electrified vehicles in Europe: expert opinion elicitation,” Technological Forecasting and Social Change, Vol.79, No.9, pp. 1622–1637, 2012.
  58. [58]  D. Zuehlke, “Smart Factory – Towards a factory-of-things,” Annual Reviews in Control, Vol.34, No.1, pp. 129–138, 2010.

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