Skip to main content

Advertisement

Springer Nature Link
Log in

A simulation-based approach for plant layout design and production planning

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Facing the new trend of Industry 4.0, manufacturing factories are required to have a more flexible structure to finish producing customized products within the limited time and at a reasonable cost. Although virtual factory technology is believed to be helpful for plant layout design and production planning, there still lacks a general framework and algorithms of simulation-based approach to design an optimized plant layout and the production process. This paper proposes a framework of simulation-based approach and develops a procedure for the implementation of the proposed framework. The paper also integrates mathematical algorithms and heuristic methods when applying simulation to balance the operation performance and the planning cost. An illustrative case demonstrates that the proposed approach can achieve the goal of better plant layout design and production planning.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Alahmari A, Abidi MH, Ahmad A, Darmoul S (2016) Development of a virtual manufacturing assembly simulation system. Adv Mech Eng 8(3):1–13

    Google Scholar 

  • Automod (2017) http://www.appliedmaterials.com. Accessed 17 Dec 2017

  • CATIA V6 (2017) https://www.3ds.com/products-services/catia/products/v6/. Accessed 07 Oct 2017

  • Dasgupta D, Michalewicz Z (2013) Evolutionary algorithms in engineering applications. Springer, Berlin

    MATH  Google Scholar 

  • Ducloux R (2014) Improvement of part or tooling life prediction through simulation of whole manufacturing process. Procedia Eng 81:504–509

    Article  Google Scholar 

  • Grienitz V, Hausicke M, Goerzel S, Dangelmaier W, Laroque C (2013) Systemic manufacturing process modelling and optimization with integrated simulation. In: A. Klass (ed) Simulation in Produktion Und Logistk 2013, pp 99–108

  • Groover MP (2007) Fundamentals of modern manufacturing: materials processes, and systems. Wiley, Hoboken

    Google Scholar 

  • Kia R, Khaksarhaghani F, Javadian N, Tavakkolimoghaddam R (2014) Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm. J Manuf Syst 33(1):218–232

    Article  Google Scholar 

  • Lenin N, Siva Kumar M, Islam MN, Ravindran D (2013) Multi-objective optimization in single-row layout design using a genetic algorithm. Int J Adv Manuf Technol 67(5–8):1777–1790

    Article  Google Scholar 

  • Li GQ, Zhao FQ, Guo C, Teng HF (2006) Parallel hybrid PSO-GA algorithm and its application to layout design. In: International conference on natural computation. Springer, Berlin, Heidelberg, 749–758

    Chapter  Google Scholar 

  • Lin MH, Fu LC (2001) A virtual factory based approach to on-line simulation and scheduling for an FMS and a case study. J Intell Manuf 12(3):269–279

    Article  Google Scholar 

  • Lindskog E, Vallhagen J, Berglund J, Johansson B (2016) Improving lean design of production systems by visualization support. Procedia CIRP 41:602–607

    Article  Google Scholar 

  • Liu XX, Liu QY, Wang W (2013) Development of virtual simulation in manufacturing industry. In: Applied mechanics and materials. Trans Tech Publ, Switzerland

    Google Scholar 

  • Molano JIR, Lovelle JMC, Montenegro CE, Granados JJR, Crespo RG (2017) Metamodel for integration of Internet of Things, Social Networks, the Cloud and Industry 4.0. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-017-0469-5

    Google Scholar 

  • Mourtzis D, Doukas M, Bernidaki D (2014) Simulation in manufacturing: review and challenges. Procedia CIRP 25:213–229

    Article  Google Scholar 

  • Mujber TS, Szecsi T, Hashmi MS (2004) Virtual reality applications in manufacturing process simulation. J Mater Process Technol 155:1834–1838

    Article  Google Scholar 

  • Pahl G, Beitz W, Feldhusen J, Grote KH (2007) Engineering design: a systematic approach. Springer, Berlin

    Book  Google Scholar 

  • Plant Simulation (2017) https://www.plm.automation.siemens.com. Accessed 07 Oct 2017

  • Promodel (2016) Simulation Conversations with ProModel. 2016. https://blog.promodel.com. Accessed 07 Oct 2017

  • Promodel (2017) https://www.promodel.com/Products/ProModel. Accessed 07 Oct 2017

  • Rong H (2011) Design of automatic block section signalling layout of appling chaos embedded particle swarm optimization algorithm based on skew tent map. Inf Control, Autom Robot 132:785–792 (Lecture Notes in Electrical Engineering book series)

    Google Scholar 

  • Siano P, Graditi G, Atrigna M, Piccolo A (2013) Designing and testing decision support and energy management systems for smart homes. J Ambient Intell Humaniz Comput 4(6):651–661

    Article  Google Scholar 

  • Suh NP (2001) Axiomatic design: advances and applications. Oxford University Press, Oxford

    Google Scholar 

  • Tao F, Qi Q (2017a) New IT driven service-oriented smart manufacturing: framework and characteristics. IEEE Trans Syst Man Cybern Syst. https://doi.org/10.1109/TSMC.2017.2723764

    Google Scholar 

  • Tao F, Zhang M (2017e) Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing. IEEE Access 5:20418–20427

    Article  Google Scholar 

  • Tao F, Zhao D, Hu Y, Zhou Z (2008) Resource service composition and its optimal-selection based on particle swarm optimization in manufacturing grid system. IEEE Trans Industr Inf 4(4):315–327

    Article  Google Scholar 

  • Tao F, Guo H, Zhang L, Cheng Y (2012) Modelling of combinable relationship-based composition service network and theoretical proof of its scale-free characteristics. Enterp Inf Syst 6(4):373–404

    Article  Google Scholar 

  • Tao F, Zuo Y, Xu LD, Zhang L (2014) IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans Industr Inf 10(2):1547–1557

    Article  Google Scholar 

  • Tao F, Cheng JF, Cheng Y, Gu SX, Zheng TY, Yang H (2017b) SDMSim: a manufacturing service supply–demand matching simulator under cloud environment. Robot Comput Integr Manuf 45(6):34–46

    Article  Google Scholar 

  • Tao F, Cheng J, Qi Q (2017c) IIHub: an industrial internet-of-things hub towards smart manufacturing based on cyber-physical system. IEEE Trans Industr Inf. https://doi.org/10.1109/TII.2017.2759178

    Google Scholar 

  • Tao F, Cheng J, Qi Q, Zhang M, Zhang H, Sui F (2017d) Digital twin-driven product design, manufacturing and service with big data. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-017-0233-1

    Google Scholar 

  • Terkaj W, Tolio T, Urgo M (2015) A virtual factory approach for in situ simulation to support production and maintenance planning. CIRP Ann Manuf Technol 64(1):451–454

    Article  Google Scholar 

  • Ullman DG (2017) The mechanical design process. McGraw-Hill, New York

    Google Scholar 

  • Yang T, Kuo Y, Su C, Hou C (2015) Lean production system design for fishing net manufacturing using lean principles and simulation optimization. J Manuf Syst 34:66–73

    Article  Google Scholar 

  • Yap HJ, Taha Z, Dawal SZ, Chang S (2014) Virtual reality based support system for layout planning and programming of an industrial robotic work cell. PloS One 9(10):e109692

    Article  Google Scholar 

  • Yildiz AR (2013) A new hybrid artificial bee colony algorithm for robust optimal design and manufacturing. Appl Soft Comput 13(5):2906–2912

    Article  Google Scholar 

  • Zhang ZN, Liu G, Jiang ZC, Chen Y (2015) A cloud-based framework for lean maintenance, repair, and overhaul of complex equipment. J Manuf Sci Eng 137(4):040908

    Article  Google Scholar 

Download references

Acknowledgements

This research is partially supported by the Ministry of Industry and Information Technology of the People’s Republic of China (2016ZXFM03002), the Shanghai Academy of Space Technology-Shanghai Jiao Tong University Joint Research Center of Advanced Aerospace Technology (USCAST2016-16) and National Key Technology Support Program (2015BAF18B02). Special thanks to Mr. Weimin Ding for the case study.

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Zhinan Zhang

  2. Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Pokfulam, Hong Kong, China

    Xin Wang

  3. Shanghai Spaceflight Manufacture (Group) Co., Ltd, Shanghai, 200245, China

    Xiaohan Wang, Fan Cui & Hui Cheng

Authors
  1. Zhinan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaohan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fan Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hui Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhinan Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Z., Wang, X., Wang, X. et al. A simulation-based approach for plant layout design and production planning. J Ambient Intell Human Comput 10, 1217–1230 (2019). https://doi.org/10.1007/s12652-018-0687-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-018-0687-5

Keywords