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Simulation and the Fourth Industrial Revolution Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Distributed Simulation of Supply Chains in the Industry 4.0 Era: A State of the Art Field Overview

Authors : Korina Katsaliaki, Navonil Mustafee

Published in: Simulation for Industry 4.0

Publisher: Springer International Publishing

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Abstract

Simulation approaches have long been used in the context of supply-chain management (SCM). Unlike the conventional approach which models the different stages of SC as a single simulation, a distributed supply-chain simulation (DSCS) enables coordinated execution of existing models through use of distributed simulation middleware. The new era of Industry 4.0 has created the “smart factory” of cyber-physical systems which controls the route of products’ assembly line for customised configuration. The collaboration of all supply-chain players in this process is essential for the tracking of a product from suppliers to customers. Therefore, it becomes necessary to examine the role of distributed simulation in designing, experimenting and prototyping the implementation of the large number of highly interconnected components of Industry 4.0 and overcome computational and information disclosure problems amongst supply chain echelons. In this chapter, we present an overview and discuss the motivation for using DSCS, the modelling techniques, the distributed computing technologies and middleware, its advantages, as also limitations and trade-offs. The aim is to inform the organizational stakeholders, simulation researchers, practitioners, distributed systems’ programmers and software vendors, as to the state of the art in DSCS which is fundamental in the complex interconnected and stochastic environment of Industry 4.0.

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previous chapter Traditional Simulation Applications in Industry 4.0
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Literature
1.
Archibald G, Karabakal N, Karlsson P (1999) Supply chain vs. supply chain: using simulation to compete beyond the four walls. In: Proceedings of the 31 st winter simulation conference, Phoenix, Arizona, USA, December 1999
2.
Bandinelli R, Rapaccini M, Tucci M, Visintin F (2006) Using simulation for supply chain analysis: reviewing and proposing distributed simulation frameworks. Prod Plann Control 17 (2):167–175. ISSN 0953-7287 CrossRef
3.
Bandinelli R, Orsoni A (2005) A DSs simulation model for outsourcing strategies in large-scale manufacturing. In: Proceedings of the 19th European conference on modelling and simulation (ECMS), 1-84233-112-4, Riga Latvia, March 2005
4.
Banks J, Buckley S, Jain S, Lendermann P, Manivannan M (2002) Opportunities for simulation in supply chain management. In: Proceedings of the 34th winter simulation conference, ISBN 0-7803-7615-3, San Diego CA, December 200
5.
Boer CA (2005) Distributed simulation in industry. Ph.D. thesis. Erasmus Research Institute of Management (ERIM), Erasmus University Rotterdam, The Netherlands
6.
7.
Chandy KM, Misra J (1979) Distributed simulation: a case study in design and verification of distributed programs. IEEE Trans Softw Eng 5(5):440–452 MathSciNetMATHCrossRef
8.
Chandy KM, Misra J (1981) Asynchronous distributed simulation via a sequence of parallel computations. Commun ACM 24(11):198–206 MathSciNetCrossRef
9.
Chapman RL, Corso M (2005) From continuous improvement to collaborative innovation: the next challenge in supply chain management. Prod Plann Control 16(4):339–344 CrossRef
10.
Chen Y, Fowler J, Wu T, Callarman T, Ambrose E, Hargaden V (2006) An adaptive distributed simulation framework for a server fulfillment supply chain. In: Proceeding of the 2006 IEEE international conference on automation science and engineering, ISBN 9781424403103, Shanghai PEOPLES R CHINA, October 2006
11.
Chong CS, Lendermann P, Gan BP, Duarte BM, Fowler JW, Callarman TE (2004) Analysis of a customer demand driven semiconductor supply chain in a distributed simulation test bed. In: Proceedings of the 2004 winter simulation conference, ISBN 0-7803-8786-4, Washington, DC USA, December 2004
12.
Chong CS, Lendermann P, Gan BP, Duarte BM, Fowler JW, Callarman TE (2006) Development and analysis of a customer-demand-driven semiconductor supply chain model using the high level architecture. Int J Simul Process Model 2(3–4):210–221 CrossRef
13.
Dalal MA, Bell H, Denzien M, Keller MP (2003) Supply chain management simulation: initializing a distribution supply chain simulation with live data. In: Proceedings of the 35th conference on winter simulation: driving innovation. Winter simulation conference, pp 1621–1626
14.
Enjalbert S, Archimède B, Charbonnaud P (2011) Distributed simulation of virtual workshops for the multi-site scheduling feasibility evaluation. Int J Prod Res 49(22):6663–6676 CrossRef
15.
Eriskin L, Gunal MM (2019) Test and evaluation for weapon systems: concepts and processes. Operations Research for Military Organizations. IGI Global, 98–110
16.
Fayez M, Rabelo L, Mollaghasemi M (2005) Ontologies for supply chain simulation modelling. In: Proceedings of the 2005 winter simulation conference, vols 1–4. ISSN 2364-2370
17.
Fischer MC, Adams A, Miller G (1994) Aggregate level simulation protocol (ALSP)—training for the future. In: Proceedings of the 1994 military operations research symposium. Military Operations Research Society (MORS), ISBN ADB 207 559, Colorado USA, June 1994
18.
Fujimoto RM (1990) Parallel discrete event simulation. Commun ACM 33(10):30–53 CrossRef
19.
Fujimoto RM (2000) Parallel and distributed simulation systems. Wiley Interscience, ISBN 978-0-471-18383-9, US
20.
Fujimoto RM, Perumalla KS, Riley GF (2007) Network simulation. Morgan & Claypool Publishers, ISBN 1598291106, Berkeley, US
21.
Fujimoto RM (1999) Parallel and distributed simulation. In: Proceedings of the 31st winter simulation conference. Phoenix AZ, USA, December 1999
22.
Fujimoto RM (2003) Distributed simulation systems. In: Proceedings of the 31st winter simulation conference. ISBN 0-7803-8132-7, New Orleans, Louisiana, USA, December 2003
23.
Fujimoto R (2015) Parallel and distributed simulation. In: Proceedings of the 2015 winter simulation conference. IEEE Press, pp 45–59
24.
Gan BP, Turner SJ (2000) Distributed supply chain simulation across enterprise boundaries. In: Proceedings of the 32nd winter simulation conference. ISBN 0-7803-1381-X, Orlando FL, USA, December 2000
25.
Gan BP, Lendermann P, Low MYH, Turner SJ, Wang X, Taylor SJ (2005) Interoperating autosched AP using the high level architecture. In: Proceedings of the 37th conference on winter simulation. Winter simulation conference, pp 394–401
26.
Hibino H, Fukuda Y, Yura Y, Mitsuyuki K, Kaneda K (2002) Manufacturing adapter of distributed simulation systems using HLA. In: Proceedings of the 34th winter simulation conference. ISBN 0-7803-7615-3, San Diego CA, USA, December 2002
27.
Hongyu J, Xia L, Yan C (2010) The research of a distributed simulation method of information sharing in supply chain. In: Proceedings of 2010 international conference on optoelectronics and image processing (ICOIP 2010). ISBN 978-0-7695-4252-2, Haiko China, November 2010
28.
Iannone R, Miranda S, Riemma S (2007) Supply chain distributed simulation: An efficient architecture for multi-model synchronization. Simul Model Pract Theory 15:221–236 CrossRef
29.
IEEE 1516 (2000) IEEE standard for modelling and simulation (M&S) high level architecture (HLA). Institute of Electrical and Electronics Engineers, New York
30.
Jahangirian M, Eldabi T, Naseer A, Stergioulas LK, Young T (2009) Simulation in manufacturing and business: a review. Eur J Oper Res 203(1):1–13 CrossRef
31.
Jain S, Riddick F, Craens A, Kibira D (2007) Distributed simulation for interoperability testing along the supply chain. In: Proceedings of the 2007 winter simulation conference, Washington, DC USA. ISBN 1-4244-1306-0, December 2007
32.
Jefferson DR (1985) Virtual time. ACM Trans Program Lang Syst 7(3):404–425 CrossRef
33.
Katsaliaki K, Mustafee N, Taylor SJE, Brailsford S (2009) Comparing conventional and distributed approaches to simulation in a complex supply-chain health system. J Oper Res Soc 60(1):43–51 MATHCrossRef
34.
Kiralp R, Venkatadri U (2010) DSOPP: a platform for distributed simulation of order promising protocols in supply chain networks. Prod Plann Control 21(6):562–580 CrossRef
35.
Labarthe O, Espinasse B, Ferrarini A, Montreuil B (2007) Toward a methodological framework for agent-based modelling and simulation of supply chains in a mass customization context. Simul Model Pract Theory 15(2):113–136 CrossRef
36.
Lee S, Wysk RA (2004) A top-down mapping and federated-based coordination for supply chain management systems using an ERP system. In: Proceedings of the 8th world multi-conference on systemics, cybernetics and informatics. ISBN 980-6560-13-2, Naddeo, July 2004
37.
Lee S, Zhao X, Shendarkar A, Vasudevan K, Young-Jun S (2008) Fully dynamic epoch time synchronisation method for distributed supply chain simulation. Int J Comput Appl Technol 31(3–4):249–262 CrossRef
38.
Li J, Yuan A, Wu Q (2010) A framework of simulation for cluster supply chain collaboration. In: Proceedings of the 2010 international conference on internet technology and applications (iTAP 2010). ISBN 978-0-946881-54-3, Wuhan, China, August 2010
39.
Linn RJ, Chen CS, Lozan JA (2002) Development of distributed simulation model for the transporter entity in a supply chain process. In: Proceedings of the 34th winter simulation conference. ISBN 0-7803-7615-3, San Diego CA, USA, December 2002
40.
41.
Long Q, Lin J, Sun Z (2011) Modeling and distributed simulation of supply chain with a multi-agent platform. Int J Adv Manufact Technol 55(9–12):1241–1252 CrossRef
42.
Long Q, Zhang W (2014) An integrated framework for agent based inventory–production–transportation modeling and distributed simulation of supply chains. Inf Sci 277:567–581 CrossRef
43.
Makatsoris HC, Chang YS, Richards HD (2004) Design of a distributed order promising system and environment for a globally dispersed supply chain. Int J Comput Integr Manuf 17(8):679–691 CrossRef
44.
Mao W, Zheng FT, Mao J (2006) Research on simulating optimization of distributed sharing information model for food supply chain. In: Proceedings of the distributed computing and applications to business, engineering and science: international symposium, Hangzhou PEOPLES R CHINA, vols 1 and 2, pp 864–866
45.
Maturana F, Shen W, Norrie DH (1999) MetaMorph: an adaptive agent-based architecture for intelligent manufacturing. Int J Prod Res 37(10):2159–2173 MATHCrossRef
46.
McLean C, Riddick F (2000) The IMS MISSION architecture for distributed manufacturing simulation. In: Proceedings of the 32nd winter simulation conference. Orlando FL, USA, December 2000
47.
Mertins K, Rabe M, Jakel FW (2005) Distributed modelling and simulation of supply chains. Int J Comput Integr Manuf 18(5):342–349 CrossRef
48.
Miller DC, Thorpe JA (1995) SIMNET: the advent of simulator networking. Proc IEEE 83(8):1114–1123 CrossRef
49.
Mustafee N (2004) Performance evaluation of interoperability methods for distributed simulation. M.Sc. thesis. Department of Information Systems, Computing and Mathematics, Brunel University, UK
50.
51.
Mustafee N, Katsaliaki K, Taylor SJ (2014) A review of literature in distributed supply chain simulation. In: Simulation conference (WSC), 2014 winter. IEEE, pp 2872–2883
52.
Mustafee N, Sahnoun M, Smart A, Godsiff P (2015) An application of distributed simulation for hybrid modeling of offshore wind farms. In: Proceedings of the 2015 ACM SIGSIM/PADS conference on principles of advanced discrete simulation, 10–12 June 2015, London, UK. ACM, pp 171–172
53.
Mustafee N, Taylor SJE (2006) Investigating distributed simulation with COTS simulation packages: experiences with Simul8 and the HLA. In: Proceedings of the 2006 operational research society simulation workshop (SW06). ISBN 1356-3548, Leamington Spa, UK. March 2006
54.
Mustafee N, Taylor S, Katsaliaki K, Dwivedi Y, Williams M (2012) Motivations and barriers in using distributed supply chain simulation. Int Trans Oper Res 19(5):733–751 CrossRef
55.
Mustafee N, Taylor SJE, Katsaliaki K, Brailsford S (2009) Facilitating the analysis of a UK NBS chain using the HLA. Simul Trans Soc Modell Simul Int 85(2):113–128
56.
Nfaoui EH, Beqqali OE, Ouzrout Y, Bouras A (2006) An approach of agent-based distributed simulation for supply chains: negotiation protocols between collaborative agents. In: Proceedings of the 2006 European simulation and modelling conference. ISBN 0-9553018-1-5, Bonn, Germany, May 2006
57.
Nicol D, Heidelberger P (1996) Parallel execution for serial simulators. ACM Trans Modell Comput Simul 6(3):210–242 MATHCrossRef
58.
Nurmilaakso JM (2004) Supply chain scheduling using distributed parallel simulation. J Manufact Technol Manage 15(8):756–770 CrossRef
59.
Pan K, Turner SJ, Cai W, Li Z (2007) A service oriented HLA RTI on the grid. In: Proceedings of the IEEE international conference on web services. ISBN 0-7695-2924-0, Salt Lake City, Utah, USA, July 2007
60.
Pannirselvam GP, Ferguson LA, Ash RC, Siferd SP (1999) Operations management research: an update for the 1990s. J Operat Manage 18(1):95–112 CrossRef
61.
Pidd M (2004) Systems modelling: theory and practice. Wiley, New York. ISBN 0470867329, USA
62.
Qing-qi L, Jie L (2009) Design and realization of multi-Agent-based distributed simulation system for supply chain. J Comput Appl 9:2556–2561
63.
Rabe M, Jäkel FW (2003) On standardization requirements for distributed simulation in production and logistics. Building the knowledge economy, Twente. IOS Press, The Netherlands, pp 399–406
64.
Rabe M, Jaekel FW, Weinaug H (2006) Reference models for supply chain design and configuration. In: Proceedings of the 2006 winter simulation conference. ISBN 1-4244-0501-7, Monterey, CA USA, December 2006
65.
Reynolds PF (1988) A spectrum of options for parallel simulation. In: Proceedings of the 20th winter simulation conference. ISBN 0-911801-42-1, New York, NY, USA, December 1988
66.
Robinson S (1994) Successful simulation: a practical approach to simulation projects. McGraw-Hill Companies, USA. ISBN 0077076222
67.
Rossetti MD, Chen Y (2012) A cloud computing architecture for supply chain network simulation. In: Proceedings of the winter simulation conference. Winter simulation conference, p 284
68.
Royston P (1999) The use of fractional polynomials to model continuous risk variables in epidemiology. Int J Epidemiol 28(5):964–974 CrossRef
69.
Saad SM, Terrence P, Wickramarachchi R (2003) Simulation of distributed manufacturing enterprises: a new approach. In: Proceedings of the 2003 winter simulation conference. ISBN 0-7803-8132-7, New Orleans, Louisiana, USA, December 2003
70.
Santa-Eulalia LA, D’Amours S, Frayret JM (2012) Agent-based simulations for advanced supply chain planning and scheduling: The FAMASS methodological framework for requirements analysis. Int J Comput Integr Manuf 25(10):963–980 CrossRef
71.
Sterman JD (1989) Modeling managerial behavior: misperceptions of feedback in a dynamic decision making experiment. Manage Sci 35(3):321–339 CrossRef
72.
Sterman JD (2001) System dynamics modelling: tools for teaching in a complex world. Calif Manag Rev 43(4):8–25 CrossRef
73.
Stevens GC (1989) Integrating the supply chain. Int J Phys Distrib Mater Manage 19:3–8
74.
Straßburger S (2001) Distributed simulation based on the high level architecture in Civilian application domains. Society for Computer Simulation International, Ghent
75.
Sun ZX, Lin J (2010) A system for data processing on supply-chain distributed simulation platform based on agent. Appl Mech Mater 26:397–400 CrossRef
76.
Taejong Y, Kyungdoc K, Sunyoung S, Hyunbo C, Yucesan E (2009) Applying Web services technology to implement distributed simulation for supply chain modeling and analysis. In: Proceedings of the 2009 winter simulation conference. ISBN 978-1-4244-5771-7, Austin, TX USA, December 2009
77.
Tammineni S, Venkateswaran J (2007) Advanced look-ahead based approach (ALBA) for distributed simulation of supply chains. In: Proceedings of the 2007 IEEE international conference on industrial engineering and engineering management. ISBN 078-1-4244-1529-8, Singapore, December 2007
78.
Taylor SJE, Sudra R, Janahan T, Tan G, Ladbrook J (2002) GRIDS-SCF: an infrastructure for distributed supply chain simulation. Simulation 78(5):312–320 CrossRef
79.
Taylor SJE, Bohli L, Wang X, Turner SJ, Ladbrook J (2005a) Investigating distributed simulation at the Ford Motor Company. In: Boukerche A, Turner SJ (eds) Proceedings of the ninth IEEE international symposium on distributed simulation and real-time applications. ISBN 978-0-7695-3273-8, Montreal Quebec, October 2005
80.
Taylor SJE, Turner SJ, Low MYH (2005b) The COTS simulation interoperability product development group. In: Proceedings of the 2005 European simulation interoperability workshop. ISBN 0309067421, Toulouse France, June 2005
81.
Taylor SJ, Fujimoto R, Page EH, Fishwick PA, Uhrmacher AM, Wainer G (2012a) Panel on grand challenges for modeling and simulation. In: Proceedings of the winter simulation conference. Winter simulation conference, p 232
82.
Taylor SJ, Turner SJ, Strassburger S, Mustafee N (2012) Bridging the gap: a standards-based approach to OR/MS distributed simulation. ACM Trans Model Comput Simul (TOMACS) 22(4):18 MathSciNetCrossRef
83.
Taylor SJE, Wang X, Turner SJ, Low MYH (2006) Integrating heterogeneous distributed COTS discrete-event simulation packages: an emerging standards-based approach. IEEE Trans Syst Man Cybernet: Part A 36(1):109–122 CrossRef
84.
Terzi S, Cavalieri S (2004) Simulation in the supply chain context: a survey. Comput Ind 53(1):3–16 CrossRef
85.
Tjahjono B, Esplugues C, Ares E, Pelaez G (2017) What does industry 4.0 mean to supply chain? Procedia Manufact 13:1175–1182 CrossRef
86.
Turner SJ, Cai W, Gan BP (2009) Adapting a supply-chain simulation for HLA. In: Proceedings of the 4th IEEE international workshop on distributed simulation and real-time applications (DS-RT’00). ISBN 0-7695-0837-5, California, US, August 2009
87.
Venkateswaran J, Son YJ (2005) Hybrid system dynamic-discrete event simulation-based architecture for hierarchical production planning. Int J Prod Res 43(20):4397–4429. ISSN 0020-7543 CrossRef
88.
Venkateswaran J, Son YJ, Jones AT, Min HSJ (2006) A hybrid simulation approach to planning in a VMI supply chain. Int J Simul Process Model 2(3–4):133–149 CrossRef
89.
Venkateswaran J, Son Y (2009) Robust supply-chain planning using multi-resolution hybrid models: experimental study. Int J Model Simul 29(4):417–427 CrossRef
90.
Wen-guang W, Jie L (2009) Research of MAS-based distributed simulation platform for supply chain. J Syst Simul 10:6099–6143
91.
Xu J, Huang E, Hsieh L, Lee LH, Jia QS, Chen CH (2016) Simulation optimization in the era of industrial 4.0 and the industrial internet. J Simul 10(4):310–320 CrossRef
92.
Xu X, Lin J (2009) A novel time advancing mechanism for agent-oriented supply chain. J Comput 12(12):1301–1308 MathSciNet
93.
Yoo T, Cho H, Yücesan E (2010) Hybrid algorithm for discrete event simulation based supply chain optimization. Expert Syst Appl 37(3):2354–2361 CrossRef
Metadata
Title
Distributed Simulation of Supply Chains in the Industry 4.0 Era: A State of the Art Field Overview
Authors
Korina Katsaliaki
Navonil Mustafee
Copyright Year
2019
Book
Simulation for Industry 4.0

Print ISBN: 978-3-030-04136-6

Electronic ISBN: 978-3-030-04137-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-04137-3_4

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