Optimal K-unit cycle scheduling of two-cluster tools with residency constraints and general robot moving times

Li, Xin; Fung, Richard Y. K.

doi:10.1007/s10951-015-0448-7

Cited by 16 publications

(3 citation statements)

References 34 publications

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“…Microchip manufacturing scheduling problems have been researched from various points of view. Scheduling robotic arms of two-cluster tools in microchip manufacturing facilities [13], transport scheduling in automated material handling systems for wafer manufacturing plants [14], wafer production scheduling as a job shop scheduling problem [15]. In this paper the research focus is on the resource constrained production scheduling.…”

Section: B Microchip Manufacturingmentioning

confidence: 99%

Dynamic impact for ant colony optimization algorithm

Skackauskas

Kalganova

Dear

et al. 2022

Swarm and Evolutionary Computation

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Section: B Microchip Manufacturingmentioning

confidence: 99%

Dynamic impact for ant colony optimization algorithm

Skackauskas

Kalganova

Dear

et al. 2022

Swarm and Evolutionary Computation

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“…(Lee, Kim, and Lee 2015) examined concurrent processing of two different types of wafer lots by developing efficient robot task sequences. (Li and Fung 2016) considered two-cluster tools with residency time constraints and derived a mathematical programming model for optimal K-unit cyclic schedules. (Kim, Lee, and Lee 2016) examined the schedulability of given schedules with time window constraints and bounded time variations by modeling the problem with Petri nets.…”

Section: Literature Reviewmentioning

confidence: 99%

Backward Sequence Analysis for Single-Armed Cluster Tools

Lee

Kim

2019

ICAPS

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This paper analyzes a backward sequence for single-armed cluster tools with processing time variations. A fundamental cycle is defined with the backward sequence, and a formula for the cycle time is derived by considering processing time variations. Then conditions for which the backward sequence is optimal are developed. The upper bound on the average cycle time from the backward sequence is also analyzed. We then show experimentally that the sequence performs well even with processing time variations.

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“…Presently, the main goal of the FLP is to improve manufacturing efficiency. In line with this, a number of authors suggested different objective functions for facility-layout problems, e.g., to maximize the throughput rate and minimize the conveyance time per trip [3] or minimize cycle times in order to increase productivity [4], and so forth.…”

Section: Introductionmentioning

confidence: 99%

Calibration of GA Parameters for Layout Design Optimization Problems Using Design of Experiments

Modrák

Sudhakarapandian

Semanco³

2021

Applied Sciences

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In manufacturing-cell-formation research, a major concern is to make groups of machines into machine cells and parts into part families. Extensive work has been carried out in this area using various models and techniques. Regarding these ideas, in this paper, experiments with varying parameters of the popular metaheuristic algorithm known as the genetic algorithm have been carried out with a bi-criteria objective function: the minimization of intercell moves and cell load variation. The probability of crossover (A), probability of mutation (B), and balance weight factor (C) are considered parameters for this study. The data sets used in this paper are taken from benchmarked literature in this field. The results are promising regarding determining the optimal combination of the genetic parameters for the machine-cell-formation problems considered in this study.

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Optimal K-unit cycle scheduling of two-cluster tools with residency constraints and general robot moving times

Cited by 16 publications

References 34 publications

Dynamic impact for ant colony optimization algorithm

Dynamic impact for ant colony optimization algorithm

Backward Sequence Analysis for Single-Armed Cluster Tools

Calibration of GA Parameters for Layout Design Optimization Problems Using Design of Experiments

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