Dispatching for make-to-order wafer fabs with machine-dedication and mask set-up characteristics

Wu, Muh-Cherng; Chiou, Shau Jie; Chen, Chen Fu

doi:10.1080/00207540601085919

Cited by 18 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…That is, the stepper scheduling problem may vary due to the inclusion of different constraints imposed on the steppers -for example, mask setup (Chern andLiu 2003, Duwayri et al 2006), machine dedication (Wu et al 2006(Wu et al , 2008a(Wu et al , 2008b, rework (Sha et al 2006), and cluster tool configuration (Morrison and Martin 2007). Nonetheless, these previous studies implicitly assumed that the production systems are in a highyield status.…”

Section: Literature Reviewmentioning

confidence: 94%

Scheduling semiconductor in-line steppers in new product/process introduction scenarios

Chiou

2009

International Journal of Production Research

Self Cite

View full text Add to dashboard Cite

This paper presents a scheduling method for an in-line stepper operating in a new process/production introduction (NPI) scenario. An in-line stepper is a bottleneck machine in a semiconductor fab. Its interior is comprised of a series of chambers, while its exterior is a dock equipped with a limited number of ports. The transportation unit for each chamber is a piece of wafer, while that for each port is a job that can contain up to 25 wafers. This transportation incompatibility may lead to an unexpected capacity loss for an in-line stepper -in particular in an NPI scenario that, by nature, includes a substantial number of small-sized jobs. Such a capacity loss can be alleviated by effective scheduling. A genetic algorithm (GA) scheduling method is proposed to enhance the productivity of in-line steppers. Four other sequencing methods are compared with the GA method. Numeric experiments indicate that the GA method outperforms the four benchmarks. The higher the percentage of small-sized jobs, the better the performance of the GA.

show abstract

Section: Literature Reviewmentioning

confidence: 94%

Scheduling semiconductor in-line steppers in new product/process introduction scenarios

Chiou

2009

International Journal of Production Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Wu, Chiou, and Chen (2008) developed a dispatching algorithm that tries to balance the output rate of each product segment with the goal of improving on-time delivery for a make-to-order semiconductor wafer fab. The showed that the algorithm outperformed the scheduling procedures favored by the company on 10 test scenarios with respect to on-time delivery rates and cycle times.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving performance of dispatch rules for daily scheduling of assembly and test operations

Jia

Bard

Chacon

et al. 2015

Computers & Industrial Engineering

View full text Add to dashboard Cite

“…As a result, an existing scheduling plan may not conform to a real-time production environment, and a rescheduling process is unavoidable. Presently, there are so many research activities concentrating on the static scheduling and dispatching of a semiconductor wafer fabrication facility (fab) [1,2] . However, relatively fewer researchers focus on their rescheduling problems.…”

Section: Introductionmentioning

confidence: 99%

A Swarm Intelligence Based Rescheduling Method for Semiconductor Wafer Fabrication Facilities

Qiao

2011

AMM

View full text Add to dashboard Cite

An effective rescheduling method takes an important role on improving the operational performance of a semiconductor wafer fabrication facility (fabs). In this paper, we propose a rescheduling method based on swarm intelligence. Firstly, we build a swarm intelligence based rescheduling model (SIRM) including an ant queen agent, multiple job ant agents and machine ant agents. Secondly, we design a rescheduling algorithm (CMRA) composed of three sub-algorithms: sub-algorithm-1 is used by an ant queen agent to transfer an existing static optimized scheduling plan into additional pheromones of job ant agents; sub-algorithm-2 and sub-algorithm-3 are used to convert scheduling related real-time information to dynamic pheromones of job ant agents and machine ant agents, respectively. Finally, a simplified semiconductor wafer fab model is used to verify and validate CMRA. The simulation results demonstrate that CMRA is superior to the original scheduling method to generate a static optimized scheduling plan with better performance on move, step and on-time operational due date rate under uncertain production environments.

show abstract

Dispatching for make-to-order wafer fabs with machine-dedication and mask set-up characteristics

Cited by 18 publications

References 19 publications

Scheduling semiconductor in-line steppers in new product/process introduction scenarios

Scheduling semiconductor in-line steppers in new product/process introduction scenarios

Improving performance of dispatch rules for daily scheduling of assembly and test operations

A Swarm Intelligence Based Rescheduling Method for Semiconductor Wafer Fabrication Facilities

Contact Info

Product

Resources

About