Skip to main content
SpringerLink
Log in

Reliability Model for AGV

  • Chapter
Autonomous Guided Vehicles

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 20))

  • 3594 Accesses

Abstract

The Material Handling System (MHS) in a manufacturing setting plays an important role in the performance of the entire system. Inadequately designed MHSs can interfere with the overall performance of the manufacturing system and lead to substantial losses in productivity and competitiveness, and to unacceptably long lead times. Among the advanced technologies available for MHSs, Automated Guided Vehicles (AGVs) have found increasing applications because of their capability to transport a variety of part types from point to point without human intervention.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Abdelmaguid, T.F., Nassef, A.O., Kamal, B.A., Hassan, M.F.: A hybrid GA/heuristic approach to the simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research 42(2), 267–281 (2004)

    Article  MATH  Google Scholar 

  • Ball, M.O., Lin, F.L.: A reliability model applied to emergency service vehicle location. Operations Research 41(1), 18–36 (1993)

    Article  MATH  Google Scholar 

  • Beamon, B.M.: Reliability in design of fixed-path material handling systems. University of Cincinnati Working Paper, Cincinnati (1995)

    Google Scholar 

  • Beamon, B.M.: Performance, reliability, and performability of material handling systems. International Journal of Production Research 36(2), 377–393 (1998)

    Article  MATH  Google Scholar 

  • Birge, J., Louveaux, F.: Introduction to Stochastic Programming. Springer, Berlin (1997)

    MATH  Google Scholar 

  • Buzacott, J.A., Yao, D.D.: Flexible manufacturing systems: A review of analytical models. Management Science 32(7), 890–905 (1986)

    Article  Google Scholar 

  • Carbone, R.: Public facilities location under stochastic demand. Infor. 12(3), 261–270 (1974)

    MATH  MathSciNet  Google Scholar 

  • Charnes, A., Cooper, W.: Chance-constraint programming. Management Science 6(1), 73–79 (1959)

    Article  MATH  MathSciNet  Google Scholar 

  • Crombecq, K., Laermans, E., Dhaene, T.: Efficient space-filling and non-collapsing sequential design strategies for simulation-based modeling. European Journal of Operational Research 214(3), 683–696 (2011)

    Article  Google Scholar 

  • Deroussi, L., Gourgand, M., Tchernev, N.: A simple metaheuristic approach to the simultaneous scheduling of machines and automated guided vehicles. International Journal of Production Research 46(8), 2143–2164 (2008)

    Article  MATH  Google Scholar 

  • Edwards, W.: How to use multiple attribute utility measurement for social decision-making. IEEE Transactions on Systems Man and Cybernetics 7(5), 326–340 (1977)

    Article  Google Scholar 

  • Farling, B.E., Mosier, C.T., Mahmoodi, F.: Analysis of automated guided vehicle configurations in flexible manufacturing systems. International Journal of Production Research 39(18), 4239–4260 (2001)

    Article  MATH  Google Scholar 

  • Gnanavel Babu, A., Jerald, J., Noorul Haq, A., Muthu Luxmi, V., Vigneswaralu, T.P.: Scheduling of machines and automated guided vehicles in FMS using differential evolution. International Journal of Production Research 48(16), 4683–4699 (2010)

    Article  MATH  Google Scholar 

  • Ho, Y.-C., Sieh, P.F.: A machine-to-loop assignment and layout design methodology for tandem AGV systems with multiple-load vehicles. International Journal of Production Research 42(4), 801–832 (2004)

    Article  MATH  Google Scholar 

  • Ho, Y.-C., Cassandras, C.G., Chen, C.-H., Dai, L.: Ordinal optimisation and simulation. Journal of the Operational Research Society 51(4), 490–500 (2000)

    Article  MATH  Google Scholar 

  • Jain, A., Jain, P.K., Chan, F.T.S., Singh, S.: A review on manufacturing flexibility. International Journal of Production Research 51(9), 5946–5970 (2013)

    Article  Google Scholar 

  • Keeney, R.L., Raiffa, H.: Decisions with Multiple Objectives: Preferences and Value Trade-offs. Wiley, New York (1976)

    Google Scholar 

  • Khosravi, A., Nahavandi, S., Creighton, D., Atiya, A.F.: Comprehensive review of neural network-based prediction intervals and new advances. IEEE Transactions on Neural Networks 22(9), 1341–1356 (2011)

    Article  Google Scholar 

  • Kleindorfer, P.R., Kunreuther, H.C., Schoemaker, P.J.H.: Decision Sciences: An Integrative Perspective. Cambridge University Press, New York (1993)

    Book  Google Scholar 

  • Kohonen, T.: An introduction to neural computing. Artificial Neural Networks 1(1), 3–16 (1988)

    Article  Google Scholar 

  • Kros, J.F., Lin, M., Brown, M.L.: Effects of the neural network s-Sigmoid function on KDD in the presence of imprecise data. Computers and Operations Research 33(11), 3136–3149 (2006)

    Article  MATH  Google Scholar 

  • Kuo, Y., Yang, T., Peters, B.A., Chang, I.: Simulation metamodel development using uniform design and neural networks for automated material handling systems in semiconductor wafer fabrication. Simulation Modelling Practice and Theory 15(8), 1002–1015 (2007)

    Article  Google Scholar 

  • Law, A.M., Kelton, W.D.: Simulation Modeling and Analysis, 2nd edn. McGraw-Hill, Singapore (2000)

    Google Scholar 

  • Le-Anh, T., De Koster, M.B.M.: A review of design and control of automated guided vehicle systems. European Journal of Operational Research 171(1), 1–23 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  • Lee, L.H., Chew, E.P., Manikam, P.: A general framework on the simulation-based optimization under fixed computing budget. European Journal of Operational Research 174(3), 1828–1841 (2006)

    Article  MATH  Google Scholar 

  • Lee, J., Tangjarukij, M., Zhu, Z.: Load selection of automated guided vehicles in flexible manufacturing systems. International Journal of Production Research 34(12), 3383–3400 (1996)

    Article  MATH  Google Scholar 

  • Maniya, K.D., Bhatt, M.G.: A multi-attribute selection of automated guided vehicle using the AHP/M-GRA technique. International Journal of Production Research 49(20), 6107–6124 (2011)

    Article  Google Scholar 

  • Maxwell, W.L., Muckstadt, J.A.: Design of automated guided vehicle systems. IIE Transactions 14(2), 114–124 (1982)

    Article  Google Scholar 

  • McCulloch, W., Pitts, W.: A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics 5, 115–133 (1943)

    Article  MATH  MathSciNet  Google Scholar 

  • Özcan, U.: Balancing stochastic two-sided assembly lines: A chance-constrained, piecewise-linear, mixed integer program and a simulated annealing algorithm. European Journal of Operational Research 205(1), 81–97 (2010)

    Article  MATH  Google Scholar 

  • Ozden: A simulation study of multiple-load carrying automated guided vehicles in a flexible manufacturing system. International Journal of Production Research 26(8), 1353–1366 (1988)

    Google Scholar 

  • Pamosoaji, A.K., Cat, P.T., Hong, K.S.: Sliding-mode and proportional-derivative-type motion control with radial basis function neural network based estimators for wheeled vehicles. International Journal of Systems Science (2013), doi:10.1080/00207721.2013.772678

    Google Scholar 

  • Pöyhönen, M., Hämäläinen, R.P.: On the convergence of multiattribute weighting methods. European Journal of Operational Research 129(3), 569–585 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  • Rosenblatt, F.: The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review 65(6), 386–408 (1958)

    Article  MathSciNet  Google Scholar 

  • Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill, New York (1980)

    MATH  Google Scholar 

  • Sarker, B.R., Gurav, S.S.: Route planning for automated guided vehicles in a manufacturing facility. International Journal of Production Research 43(21), 4659–4683 (2005)

    Article  MATH  Google Scholar 

  • Sayarshad, H.R., Tavakkoli-Moghaddam, R.: Solving a multi periodic stochastic model of the rail–car fleet sizing by two-stage optimization formulation. Applied Mathematical Modelling 34(5), 1164–1174 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  • Shiode, S., Drezner, Z.: A competitive facility location problem on a tree network with stochastic weights. European Journal of Operational Research 149(1), 47–52 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  • Smith, D.J.: Reliability, Maintainability and Risk. Butterworth Heinemann, Oxford (1993)

    Google Scholar 

  • Stewart, W., Golden, B.: Stochastic vehicle routing: A comprehensive approach. European Journal of Operational Research 14(4), 371–385 (1983)

    Article  MATH  Google Scholar 

  • Ultsch, A., Korus, D., Kleine, T.O.: Integration of Neural Networks and knowledge-based systems in medicine. In: Wyatt, J.C., Stefanelli, M., Barahona, P. (eds.) AIME 1995. LNCS, vol. 934, pp. 425–426. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

  • Von Winterfeldt, D., Edwards, W.: Decision Analysis and Behavioral Research. Cambridge University Press, Cambridge (1986)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Industrial Engineering , Iran University of Science and Technology, Tehran, Iran

    Hamed Fazlollahtabar

  2. Faculty of Industrial Engineering, Center of Excellence for Advance Manufacturing , Iran University of Science and Technology, Tehran, Iran

    Mohammad Saidi-Mehrabad

Authors
  1. Hamed Fazlollahtabar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammad Saidi-Mehrabad
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hamed Fazlollahtabar .

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Fazlollahtabar, H., Saidi-Mehrabad, M. (2015). Reliability Model for AGV. In: Autonomous Guided Vehicles. Studies in Systems, Decision and Control, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-14747-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14747-5_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14746-8

  • Online ISBN: 978-3-319-14747-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation