Dynamic Load Balancing Among Multiple Fabrication Lines Through Estimation of Minimum Inter-Operation Time

Toba, Hapnes; Izumi, Hiroyuki; Hatada, H.; Chikushima, T.

doi:10.1109/tsm.2004.840535

Cited by 25 publications

(8 citation statements)

References 9 publications

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“…The other track focused on the capacity-trading decisions between the two plants. Example studies on the route assignment decisions include Toba et al (2005) and Wu et al (2009aWu et al ( , 2009b. Example studies on the capacity-trading decisions include Wu and Chang (2007), Chen et al (2008), Chiang et al (2010) and Renna and Argoneto (2011).…”

Section: Relevant Literaturementioning

confidence: 99%

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A combined dispatching criteria approach to scheduling dual flow-shops

Chiou

Chen

Wu³

2013

International Journal of Production Research

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This study investigates a dual flow-shops scheduling problem. In the scheduling context, there are two flow shops and each shop involves three processing stages. The two shops are functionally identical but their stage processing times for a job are different. While sequentially going through the three processing stages, each job is allowed to travel between the two shops. That is, for a job, each of its three stages could be processed in any of the two shops. Such a context is called dual flow-shops in the sense that the two flow shops' capacities are completely shared. The scheduling problem involves two decisions: (1) route assignment (i.e. assigning the processing stages of a job to a shop), and (2) job sequencing (i.e. sequencing the jobs waiting before each stage). The scheduling objective is to minimise the coefficient of variation of slack time (CV S ), in which the slack time (also called lateness) denotes the difference between the due date and total completion time of a job. We propose five genetic-algorithm-based (GA-based) solution methods to solve the scheduling problem, which are called GA-EDD, GA-FIFO, GA-SPT, GA-LFO, and GA-COMBO respectively. Numerical experiments indicate that GA-COMBO outperforms the other four methods.

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Section: Relevant Literaturementioning

confidence: 99%

“…In contrast, Toba et al (2005) addressed the route assignment problem in shop floor control context; that is, how to determine the production route of a job in a real time manner by dynamically considering machine breakdown status.…”

Section: Relevant Literaturementioning

confidence: 99%

A combined dispatching criteria approach to scheduling dual flow-shops

Chiou

Chen

Wu³

2013

International Journal of Production Research

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“…Only a few studies on the route planning problem have been published. Toba et al (2005) addressed the route planning problem in a real-time manner. That is, whenever an operation of a job is completed, a decision -which fab to use to manufacture the next operation -must be made immediately.…”

Section: Introductionmentioning

confidence: 99%

Route planning for two wafer fabs with capacity-sharing mechanisms

Chen

Shih

2009

International Journal of Production Research

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This paper formulates and solves a route planning problem for semiconductor manufacturing. In order to quickly respond to rising demand, a semiconductor company usually adopts a dual-fab strategy to expand capacity. That is, two fab sites are built as neighbours and can easily share capacity. Through the capacity-sharing design, a product may be produced by a cross-fab route. That is, some operations of a product are carried out in one fab and the other operations in the other fab. This leads to a routing planning problem, which involves two decisions -determining the cut-off point of the cross-fab route and the route ratio for each product -in order to maximise the throughput subject to a cycle time constraint. An LP-GA method is proposed to solve the route planning problem. We first use the LP module to make the cut-off point decisions, and proceed to use the GA module for making the decision on the route ratio. Experimental results show that the LP-GA method significantly outperforms other methods.Keywords: operations management; operations strategy; operations planning IntroductionThe semiconductor manufacturing industry has to consider the following three factors when expanding capacity. The equipment costs are very expensive, perhaps costing over one billion dollars for a 12 inch wafer fab. The lead time for equipment acquisition is quite long, ranging from 3 to 9 months. However, building the factory space is relatively inexpensive, but with a much longer lead time -taking about one to two years.In order to respond quickly to rising demand, a semiconductor company usually adopts a dual-fab strategy to expand capacity. That is, a large-scale factory space that can accommodate two fabs is established in advance. Then, the equipment for the two fabs is gradually moved into the space over time according to market demand. The two fabs, close to each other in location, support each other and should be managed in an integrated manner.In such a dual-fab configuration, a relatively easy way to manage is to manufacture each wafer job in one fab. That is, each fab is run separately, without any mutual support in capacity. Such a separated-operation paradigm usually leads to an underutilisation of equipment. To remedy the underutilisation issue, a cross-fab production paradigm is proposed. This means that a wafer job is partly manufactured in one fab and partly manufactured in the other fab.

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“…Prior studies on such a route planning problem are relatively few. With each job route being cut into several segments, Toba, Izumi, Hatada, and Chikushima (2005) studied the route planning problem in a real-time manner. That is, whenever a segment is completed, a decision-which fab to manufacture the next segment-must be immediately made.…”

Section: Introductionmentioning

confidence: 99%