Stochastic Modeling of an Automated Guided Vehicle System with One Vehicle and a Closed-Loop Path

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, VOL. 5, NO. 3, JULY 2008

Stochastic Modeling of an Automated Guided Vehicle
System With One Vehicle and a Closed-Loop Path
Aykut F. Kahraman, Abhijit Gosavi, Member, IEEE, and Karla J. Oty

Abstract—The use of automated guided vehicles (AGVs) in material-handling processes of manufacturing facilities and warehouses is becoming increasingly common. A critical drawback of an AGV is its prohibitively high cost. Cost considerations dictate an economic design of AGV systems. This paper presents an analytical model that uses a Markov chain approximation approach to evaluate the performance of the system with respect to costs and the risk associated with it. This model
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It can also help the manager determine whether a trailer needs to be added to an existing
AGV. Of particular interest to the managers we interacted with is the issue of downside risk defined above.
As input parameters, the model requires the knowledge of the distribution of the interarrival time of jobs at each of the workstations. It also needs the mean time taken to travel from one workstation to the next. The model can be easily computerized.
The model we develop is for pick-up AGVs, which primarily pick up jobs and drop them off at a central location in the workplace. With some additional work, our models could be extended to dropoff AGVs. They could also be used for performance evaluation of people movers in amusement parks.
Index Terms—Automated guided vehicle (AGV), downside risk,
Markov chains, quality-of-service (QoS).
Manuscript received March 24, 2006; revised July 19, 2006 and November
1, 2006. This paper was recommended for publication by Associate Editor
T.-E. Lee and Editor N. Viswanadham upon evaluation of the reviewers’ comments. This work was supported in part by the National Science Foundation under Grant DMI: 0114007.
A. F. Kahraman is with Deccan International, San Diego, CA 92121 USA
(e-mail: afk3@buffalo.edu).
A. Gosavi is with the Department of Industrial Engineering, State University of New York, Buffalo, NY 14260-2050 USA (e-mail: agosavi@buffalo.edu).
K. J. Oty is with

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