Markovian Reliability in Multiple AGV System

Markovian Reliability in Multiple AGV System

Hamed Fazlollahtabar (Iran University of Science and Technology, Iran) and Mohammad Saidi-Mehrabad (Iran University of Science and Technology, Iran)
Copyright: © 2014 |Pages: 8
DOI: 10.4018/978-1-4666-5202-6.ch134

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Flexible manufacturing systems (FMS) are crucial for modern manufacturing to enhance productivity involved with high product proliferation. As one of the critical components of the FMS, the flexible material handling system (MHS) plays a strategic role in the implementation of the FMS. According to Tompkins et al. (2002), about 20–50% of the total production cost is spent on material handling. This makes the subject of material handling increasingly important. In addition, all the complexity of manufacturing are passed on to the MHS. Therefore, the flexible MHS has been vital for improving the FMS to fulfill the requirements of high product proliferation (Zhao et al., 2011).

Automated manufacturing systems (AMS), which are equipped with several CNC machines and AGV-based material handling system are designed and implemented to gain the automation and efficiency of production. To make use of all features of AMS, the planning in the AMS decision making process is critical because the planning decision has influence on the subsequent decision processes such as scheduling, dispatching, etc. The planning in automated manufacturing systems can be characterized as being online and short-term nature to respond to frequently changing production order. Given a production order, manufacturing planning function is responsible to establish a plan by decomposing the production task into a set of subtasks. An analysis of AMS dealing with changing demand can be found in (Terkaj et al., 2009). An extensive review of the loading problem for an FMS can be found in (Grieco et al., 2001). An early stochastic programming approach to address the short-term production planning for an FMS can be found in (Terkaj & Tolio, 2006).

Key Terms in this Chapter

Reliability: Reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time.

Markovian Property: A stochastic process has the Markov property if the conditional probability distribution of future states of the process depends only upon the present state, not on the sequence of events that preceded it.

Shop: Shop is an industrial unit for processing a function allocated due to the manufacturing plan using input material and delivering semi-produced or final products to the next manufacturing unit.

Stochastic Process: A statistical process involving a number of random variables depending on a variable parameter (which is usually time).

Limiting Probability: The probability that a continuous-time Markov chain will be in a specific state at a certain time often converges to a limiting value which is independent of the initial state.

Automated Guided Vehicle: An automated driverless controllable vehicle which is used as transportation and transferring device.

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