Lot Size Management in the Semiconductor Industry: Queueing Analysis for Cycle Time Optimization

Zarifoglu, Emrah; Hasenbein, John J.; Kutanoğlu, Erhan

doi:10.1109/tsm.2012.2230032

Cited by 6 publications

(2 citation statements)

References 8 publications

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“…Other factors that influence the cycle time have been used as a lever for cycle time reduction such as Work-In-process management [11], batch size [14], lot size [15] and [16], queue time management and priority management. Equipment management, essentially the study of preventive maintenance segregation, is proposed in [17] with the goal to determine the optimum preventive maintenance policy that results in reduced fabrication cycle times.…”

Section: Introductionmentioning

confidence: 99%

Push and Time at Operation strategies for cycle time minimization in global fab scheduling for semiconductor manufacturing

Barhebwa-Mushamuka

Dauzère‐Pérès

Yugma

2021

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)

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This paper investigates two global scheduling strategies for cycle time minimization in semiconductor manufacturing. These global scheduling strategies represented as a linear programming models are compared to a First-in-First out dispatching rule. The first global scheduling strategy is a Push strategy, in which products are pushed to their final operations using high Work-In-Process holding costs on the first operations. The second global scheduling strategy is a Time at Operation strategy, where Work-In-Process quantities that have arrived at different times in an operation are penalized differently. The computational results performed on industrial data using the Anylogic simulation software coupled with IBM ILOG CPLEX show that the Time at Operation strategy minimizes the cycle time while maintaining a high throughput compared to the Push strategy and the simple First-In-First-Out dispatching rule. The paper also shows, when production targets are determined using the Push strategy, products with a large number of operations are prioritized.

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Section: Introductionmentioning

confidence: 99%

Push and Time at Operation strategies for cycle time minimization in global fab scheduling for semiconductor manufacturing

Barhebwa-Mushamuka

Dauzère‐Pérès

Yugma

2021

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)

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“…To decrease the CT, Lin et al (2008) developed a formula for standard WIP to set the range of WIP level. Zarifoglu et al (2013) also developed a queueing model to gain an insight into the relationship among CT and lot size. Yaghoubi et al (2013) modelled multi-class multi-stage assembly systems with finite capacity as queueing networks to optimally control the service rates.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis and optimization of queueing network production systems considering non-conforming products rework and departure

Zhang

2018

JAMDSM

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During the past decades, the production performance analysis and optimization have played a significant role in queueing network system production planning and operation design for the manufacturing plants, but how to model the optimized production system performance and solve it is facing great challenges. Since the more and more wide use of queueing network, the non-conforming product scenarios such as rework and departure, cause mass random interference. These problems when modelled in the conventional analysis and optimization models are extremely difficult to solve as they are coupled and NP-hard problems. This paper considers a modified M/M/n/m-first come first service (M/M/n/m-FCFS) queueing network approximation model that is developed to maximize utilization and profit by analysing the queue time and queue length of the products under the constraint conditions. A hybrid meta-heuristics is applied to solve the approximation model, both the service rate and buffer allocation of the queueing network system can be determined. Finally, to assess the effectiveness of the proposed method, extensive numerical experimental results from the approximation model are compared to the ARENA simulation, and sensitivity and validation analysis are also conducted, which prove it accurate, believable, and effective.Keywords : Production planning, Operation design, Analysis and optimization, Queueing network, Non-conforming product, Hybrid meta-heuristics, Approximation model IntroductionMost manufacturing companies are facing the challenge of quickly implementing flexible and complex production systems (Walid and Ali, 2002). But the production systems often experience worse performance for the unavoidable variability exists in reality. This phenomenon appears widely in queueing network and multi-product mixed production system. Performance analysis and optimization problems in queueing systems have received considerable attention in recent years, due to their wide applicability in the performance evaluation and optimal design of manufacturing systems and computer networks (Song et al., 1998). Now, the long serial lines analysis and optimization have been well studied using decomposition (Shi and Gershwin, 2014;Damodaran and Hulett, 2012;Cauffriez and Willaeys, 2006) or aggregation (Veeger et al., 2011;Belmansour and Nourelfath, 2008) methods for a long time, and extensive results are obtained. Although many studies have focused on solving the line optimization problems, the studies in which a large number of approaches are currently applied to research the performance of queueing network systems considering the non-conforming products are still extremely limited.Research in the field of performance optimization tends to focus on issue models, such as cycle time (CT) optimization (Gilenson et al., 2015), throughput (TH) optimization (Law et al., 2008), work-in-process (WIP) optimization (Reyes et al., 2013;Qiu, 2005), and buffer allocation optimization (Shihabudin et al., 2015;Nahas, 2014). The published literature...

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Stochastic lot sizing for maximisation of shareholder wealth in make-to-order manufacturing

Choi

Wang

2014

International Journal of Production Research

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Lot Size Management in the Semiconductor Industry: Queueing Analysis for Cycle Time Optimization

Cited by 6 publications

References 8 publications

Push and Time at Operation strategies for cycle time minimization in global fab scheduling for semiconductor manufacturing

Push and Time at Operation strategies for cycle time minimization in global fab scheduling for semiconductor manufacturing

Performance analysis and optimization of queueing network production systems considering non-conforming products rework and departure

Stochastic lot sizing for maximisation of shareholder wealth in make-to-order manufacturing

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