Abstract
Modern production and logistic systems are facing increasing market dynamics: customers demand highly individualized goods, the adherence to due dates becomes critical and stipulated delivery times are decreasing. Particularly logistic networks, e.g. production networks or supply chains, are strongly affected by this trend. On the other hand, production networks have to deal with inherent internal dynamics, which are caused by e.g. machine breakdowns or rush orders. The concept of autonomous control, coming from the theory of self-organization, offers decentralized autonomous decision policies (ADPs), which enable logistic objects to make and execute decision on their own. Due to this kind of decision making, autonomous control aims at a distributed coping with dynamic complexity and, at the same time, at an improvement of the logistic performance. This contribution addresses the concept of autonomous control and the underlying autonomous decision policies as a novel concept for the control of the material flows in networks of coupled production facilities. Moreover, it shows different concepts of modeling and analysis of autonomously controlled networks. To achieve this goal, a dual approach including both, mathematical methods as well as simulation models, is presented. Subsequently, the possibilities to analyze the dynamic behavior of the autonomous logistic system are discussed, i.e., the system’s stability and its logistic performance. Finally, this contribution presents an exemplary case of a production network to demonstrate the practicability of the approach of modeling and analysis of autonomous control for production networks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Allahverdi A, Ng CT, Cheng TCE, Kovalyov M (2008) A survey of scheduling problems with setup times or costs. Eur J Oper Res 187(3):985–1032
Alvarez E (2007) Multi-plant production scheduling in SMEs. Robotics Comput Integr Manuf 23(6):608–613
Armbruster D, de Beer C, Freitag M, Jagalski T, Ringhofer Ch (2006) Autonomous control of production networks using a pheromone approach. Physica A 363(1):104–114
Banks J, Carson JS, Nelson BL, Nicol DM (2010) Discrete-event system simulation. Prentice Hall, Upper Saddle River
Bertazzi L, Speranza MG (2005) Worst-case analysis of the full load policy in the single link problem. Int J Prod Econ 93–94:217–224.
Bloos M, Kopfer H (2009) Efficiency of transport collaboration mechanisms. Commun SIWN 6(1):23–28
Camarinha-Matos L, Afsarmanesh H (2003) Elements of a base VE infrastructure. Comput Ind 51:139–163
Chahal K, Eldabi T (2010) A multi-perspective comparison for selection between system dynamics and discrete event simulation. Int J Bus Inf Syst Arch 6(1):4–17
Comelli M, Gourgand M, Lemoine D (2008) A review of tactical planning models. J Syst Sci Syst Eng 17(2):204–229
Crainic TG (2000) Service network design in freight transportation. Eur J Oper Res 122(2): 272–288
Dashkovskiy S, Rüffer B (2010) Local ISS of large-scale interconnections and estimates for stability regions. Syst Control Lett 59(3):241–247
Dashkovskiy S, Görges M, Naujok L (2009) Local input to state stability of production networks. In: Proceedings of 2nd international conference on dynamics in logistics (LDIC 2009). Springer, Bremen
Domschke W, Scholl A, Voß S (1997) Produktionsplanung. Springer, Berlin
Dunbar WB, Desa S (2007) Distributed MPC for dynamic supply chain management. Assessment and future directions of nonlinear model predictive control. Lect Notes Control Inf Sci 358:607–615
Erengünc SS, Simpson NC, Vakharia AJ (1999) Integrated production/distribution planning in supply chains. Eur J Oper Res 115(2):219–236
Fleischmann B, Gietz M (2008) Transport- und Tourenplanung. In: Arnold D, Isermann H, Kuhn A, Tempelmeier H (eds) Handbuch Logistik, Springer, Heidelberg pp 137–152
Garey MR, Johnson DS (1979) Computers and intractability: a guide to the theory of NP-completeness, Freeman, San Francisco
Gudehus T (2005) Logistik. Springer, Berlin
Guinet A (2001) Multi-site planning: a transshipment problem. Int J Prod Econ 74(3):21–32
Hinrichsen D, Pritchard AJ (2005) Mathematical systems theory I. series: texts in applied mathematics, vol 48. Springer, Berlin
Ivanov D (2009) An adaptive framework for aligning (re)planning decisions on supply chain strategy, design, tactics, and operations. Int J Prod Res 48(13):3999–4017
Jungwattanakit J, Reodecha M, Chaovalitwongse P, Werner F (2008) Algorithms for flexible flow shop problems with unrelated parallel machines, setup times, and dual criteria. Int J Adv Manuf Technol 37(3):354–370
Jungwattanakit J, Reodecha M, Chaovalitwongse P, Werner F (2009) A comparison of scheduling algorithms for flexible flow shop problems with unrelated parallel machines, setup times, and dual criteria, Comput Oper Res 36(2):358–378, Scheduling for Modern Manufacturing, Logistics, and Supply Chains
Kim J–H, Duffie NA (2004) Backlog control for a closed loop PPC system. Ann CIRP 53(1):357–360
Kuhn A., Wenzel S (2008) Simulation logisitscher systeme. In: Arnold D, Isermann H, Kuhn A, Tempelmeier H (eds) Handbuch Logistik. Springer, Berlin, pp 73–92
Martinez MT, Fouletier P, Park KH, Favrel J (2001) Virtual enterprise organisation, evolution and control. Int J Prod Econ 74(1–3):225–238
Meyr H, Wagner M, Rohde J (2005) Structure of advanced planning systems. In: Stadtler H, Kilger C (eds) Supply chain management and advanced planning. Springer, Berlin, pp 109–115
Min H, Zhou G (2002) Supply chain modeling: past, present and future. Comput Ind Eng 43(2):231–249
Morecroft J, Robinson S (2006) Comparing discrete-event simulation and system dynamics: modelling a fishery. In: Proceedings of the operational research society simulation workshop 2006. Operational research society, Birmingham, pp 137–148
Müller F, Otto A (2007) Anwendungsarchitekturen in supra-adaptiven Logistik-netzwerken. In: Günthner WA (eds) Neue Wege in der Automobillogistik: die Vision der Supra-Adaptivität; mit 14 Tabellen. Springer, Berlin, pp 149–166
Muth JF, Thompson GL (1963) Industrial scheduling. Prentice-Hall, Englewood Cliffs
Parunak HV (1997) Go to the ant: engineering principles from natural multi-agent systems. Ann Oper Res 15:69–101
Peeters P, van Brussel H, Valckenaers P, Wyns J, Bongaerts L, Kollingbaum M, Heikkilä T (2001) Pheromone based emergent shop floor control system for flexible flow shops. Artif Intell Eng 15(4):343–352
Philipp T, de Beer C, Windt K, Scholz-Reiter B (2007) Evaluation of autonomous logistic processes—analysis of the influence of structural complexity. In: Hülsmann M, Windt K (eds.) Understanding autonomous cooperation and control in Logistics—the impact on management, information and communication and material flow. Springer, Berlin, pp 303–324
Pinedo ML (2008) Scheduling—theory, algorithms, and systems. Springer, New York
Quadt D, Kuhn H (2007) A taxonomy of flexible flow line scheduling procedures. Eur J Oper Res 178(3):686–698
Rabelo L, Helal M, Lertpattarapong C, Moraga R, Sarmiento A (2008) Using system dynamics, neural nets, and eigenvalues to analyse supply chain behaviour. A case study. Int J Prod Res 46(1):51–71
Rekersbrink H, Makuschewitz T, Scholz-Reiter B (2009) A distributed routing concept for vehicle routing problems. Logist Res 1(1):45–52
Rohde J, Meyr H, Wagner M (2000) Die supply chain planning matrix. PPS Manag 5:10–15
Sauer J (2006) Modeling and solving multi-site scheduling problems. In: van Wezel W, Jorna R, Meystel A (eds.) Planning in intelligent systems: aspects, motivations and method. Wiley, Hoboken, pp 281–299
Scholz-Reiter B, Freitag M, de Beer C, Jagalski T (2005) Modelling and analysis of autonomous shop floor control. In: Proceedings of 38th CIRP International Seminar on Manufacturing Systems. Universidade Federal de Santa Catarina, Florianopolis
Scholz-Reiter B, Böse F, Jagalski T, Windt K (2007) Selbststeuerung in der betrieblichen Praxis - Ein Framework zur Auswahl der passenden Selbststeuerungsstrategie. Industrie Management 23(3):7–10
Scholz-Reiter B, de Beer C, Freitag M, Jagalski T (2008) Bio-inspired and pheromone-based shop-floor control. Int J Comput Integr Manuf 21(2):201–205
Scholz-Reiter B, Jagalski T, Bendul J (2008) Autonomous control of a shop floor based on bee’s foraging behaviour. In: Haasis, H-D, Kreowski H-J, Scholz-Reiter B (eds.) First international conference on dynamics in logistics. LDIC 2007, Springer, Berlin, pp. 415–423
Scholz-Reiter B, Mehrsai A, Görges M (2009) Handling the dynamics in logistics - adoption of dynamic behavior and reduction of dynamic effects. Asian Int J Sci Technol Prod Manuf Eng (AIJSTPME) 2(3):99–110
Scholz-Reiter B, Görges M, Philipp T (2009) Autonomously controlled production systems—Influence of autonomous control level on logistic performance. CIRP Ann Manuf Technol 58(1):395–398
Scholz-Reiter B, Görges M, Jagalski T, Mehrsai A (2009) Modelling and analysis of autonomously controlled production networks. In: Proceedings of the 13th IFAC symposium on information control problems in manufacturing (INCOM 09). Moscow, Russia, pp 850–855
Scholz-Reiter B, Rekersbrink H, Görges M (2010) Dynamic flexible flow shop problems - scheduling heuristics vs. autonomous control. CIRP Ann Manuf Technol 59(1):465–468
Scholz-Reiter B, Görges M, Jagalski T, Naujok L (2010) Modelling and analysis of an autonomous control method based on bacterial chemotaxis. In: 43rd CIRP international conference on manufacturing systems (ICMS 2010). Neuer Wissenschaftlicher Verlag, Wien, pp 699–706
Scholz-Reiter B, Lensing T, Görges M, Dickmann, L (2010) Classification of dynamical patterns in autonomously controlled logistic simulations using echo state networks. In: International conference on Harbor, Maritime and Multimodal Logistics Modelling and Simulation (HMS 2010). DIPTEM University of Genova, Genova, pp 85–92
Scholz-Reiter B, Dashkovskiy S, Görges M, Naujok L (2011) Stability analysis of autonomously controlled production networks. Int J Prod Res 49(16). DOI:10.1080/00207543.2010.505215
Stadtler H (2005) Supply chain management and advanced planning-basics, overview and challenges. Eur J Oper Res 163(3):575–588
Sydow J (2006) Management von Netzwerkorganisationen—zum Stand der Forschung. In: Sydow J (ed) Management von Netzwerkorganisationen, Gabler, Wiesbaden pp 385–469
Toth P, Vigo D (2002) An overview of vehicle routing problems. In: Toth P, Vigo D (eds.) The vehicle routing problem, SIAM monographs on discrete mathematics and applications, Philadelphia
Wagner B (2006) Hub & Spoke-Netzwerke in der Logistik, Deutscher Universitäts-Verlag/GWV-Fachverlage GmbH, Wiesbaden
Wiendahl H-P (2008) Betriebsorganisation für Ingenieure. München, Hanser
Wiendahl H-P, Lutz S (2002) Production in networks. Ann CIRP Manuf Technol 51(2):1–14
Windt K, Becker T (2009) Applying autonomous control methods in different logistic processes—a comparison by using an autonomous control application matrix. In: Proceedings of the 17th mediterranean conference on control and automation. Thessaloniki, Greece
Windt K, Hülsmann M (2007) Changing paradigms in logistics—understanding the shift from conventional control to autonomous cooperation and control. In: Hülsmann M, Windt K (eds.) Understanding autonomous cooperation and control—the impact of autonomy on management, information, communication, and material flow. Springer, Berlin, pp 4–16
Windt K, Böse F, Philipp T (2005) Criteria and application of autonomous cooperating logistic processes. In: Gao JX, Baxter DI, Sackett PJ (eds) Proceedings of the 3rd international conference on manufacturing research. Advances in manufacturing technology and management, Cranfield
Windt K, Philipp T, Böse F (2008) Complexity cube for the characterization of complex production systems. Int J Comp Integr Manuf 21(2):195–200
Zeigler BP, Praehofer H, Kim TG (2007) Theory of modeling and simulation—integrating discrete event and continuous complex dynamic systems, second edn (reprint). Academic Press, Amsterdam
Acknowledgments
This research is funded by the German Research Foundation (DFG) as part of the Collaborative Research Centre 637 ‘Autonomous Cooperating Logistic Processes: A Paradigm Shift and its Limitations’.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag London
About this chapter
Cite this chapter
Scholz-Reiter, B., Dashkowskiy, S., Görges, M., Jagalski, T., Naujok, L. (2012). Autonomous Decision Policies for Networks of Production Systems. In: Armbruster, D., Kempf, K. (eds) Decision Policies for Production Networks. Springer, London. https://doi.org/10.1007/978-0-85729-644-3_10
Download citation
DOI: https://doi.org/10.1007/978-0-85729-644-3_10
Published:
Publisher Name: Springer, London
Print ISBN: 978-0-85729-643-6
Online ISBN: 978-0-85729-644-3
eBook Packages: Business and EconomicsBusiness and Management (R0)