Simulation Metamodeling of a Maintenance Float System

Madu, Christian N.

doi:10.1007/978-1-4615-4329-9_6

Cited by 1 publication

(6 citation statements)

References 21 publications

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“…The maintenance float system studied herein is based on the illustrative example presented by Madu and Kuei (1996). This example considers a manufacturing system that operates on a 24-hour operation with several independent and identical machine tools.…”

Section: Description Of the Problemmentioning

confidence: 99%

“…Step 1 (define the maintenance float problem). The maintenance float system studied herein is illustrated in the previous subsection, the further details of this problem can be found in the literature (Madu and Kuei, 1996). Three performance measures including average equipment .…”

Section: Solution Of the Problemmentioning

confidence: 99%

“…A maintenance float system can be considered as a closed queueing network (refer to Figure 1), in which the machines alternate among operation, repair and standby status (Madu and Chanin, 1992;Madu and Kuei, 1996). In a maintenance float system (Madu and Chanin, 1992), N independent and identical machines are required to be in operation at the same time.…”

Section: Introductionmentioning

confidence: 99%

“…The intrinsic complexity in the maintenance system makes analytical models difficult for presenting the actual environment. Effective analytical approaches for large-scale systems with non-Markovian failure distributions are generally hard to obtain (Madu and Kuei, 1996). Even for small-scale systems with Markovian properties, the existing procedures require complicated algorithms and numerous iterations (Gross et al, 1983;Mani and Sarma, 1984;Madu, 1988a, b;Madu et al, 1990).…”

Section: Introductionmentioning

confidence: 99%

“…The neural metamodels are further extended to formulate a decision model for optimizing the maintenance float systems by using genetic algorithms. et al (1990), Lin (1996), Madu and Chanin (1992) and Madu and Kuei (1996) applied hybrid approaches, which combine simulation and regression metamodeling to study the maintenance float problems.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An approach to design of maintenance float systems

Chen

Tseng

2003

Integrated Manufacturing Systems

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The paper offers an intelligent approach to analyze and determine the design parameters minimizing the total cost and achieving the desired performance measures in the maintenance float systems. The expected total cost in a maintenance float system includes the cost of lost production, the cost of repair persons and the cost of standby machines. The developed design procedure integrates simulation, metamodel and genetic algorithms. Neural networks are able to approximate functions based on a set of sample data, i.e. construct metamodels from simulation results in this study. The objective of metamodels is to predict simulation responses in order to significantly reduce the amount of simulation runs. The predictive performance of neural metamodels comparably outperforms the traditional regression metamodels. The neural metamodels are further extended to formulate a decision model for optimizing the maintenance float systems by using genetic algorithms.

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Section: Description Of the Problemmentioning

confidence: 99%

Section: Solution Of the Problemmentioning

confidence: 99%