Efficient scheduling policies to reduce mean and variance of cycle-time in semiconductor manufacturing plants

1994 ◽  
Vol 7 (3) ◽  
pp. 374-388 ◽  
Author(s):  
S.C.H. Lu ◽  
D. Ramaswamy ◽  
P.R. Kumar
Keyword(s):  
Cycle Time ◽  
Semiconductor Manufacturing ◽  
Scheduling Policies ◽  
Manufacturing Plants ◽  
Mean And Variance

scholarly journals Simulation Study for Semiconductor Manufacturing System: Dispatching Policies for a Wafer Test Facility

2019 ◽  
Vol 11 (4) ◽  
pp. 1119 ◽  
Author(s):  
Hyun Joong Yoon ◽  
Junjae Chae
Keyword(s):  
Semiconductor Manufacturing ◽  
Material Handling ◽  
Parallel Machines ◽  
Sustainable Manufacturing ◽  
Test Facility ◽  
Efficient System ◽  
Scheduling Policies ◽  
Work In Process ◽  
Test Operation ◽  
Wafer Test

The manufacture of semiconductor products requires many dedicated steps, and these steps can be grouped into several major phases. One of the major steps found at the end of the wafer fabrication process is the electrical die sorting (EDS) test operation. This paper focuses on dispatching policies in an EDS test facility to reduce unnecessary work for the system. This allows the semiconductor manufacturing facility to achieve better overall efficiency, thereby contributing to sustainable manufacturing by reducing material movements, the use of testing machines, energy consumption, and so on. In the facility, wafer lots are processed on a series of workstations (cells), and the facility holds identical parallel machines. The wafers are moved by an automatic material handling system from cell to cell as well as within cells. We propose several scheduling policies consisting of intercell and intracell material movements for efficient system operation. For this, four intercell scheduling policies and two intracell scheduling policies are introduced, and the effects of combinations are tested and evaluated through simulation experiments to obtain performance measures such as cycle time and work in process. The most efficient results among the combinations are presented as a proposed scheduling policy for a given EDS test facility.

A FUZZY-NEURAL FLUCTUATION SMOOTHING RULE FOR SCHEDULING JOBS WITH VARIOUS PRIORITIES IN A SEMICONDUCTOR MANUFACTURING FACTORY

2009 ◽  
Vol 17 (03) ◽  
pp. 397-417 ◽  
Author(s):  
TOLY CHEN ◽  
YU-CHENG LIN
Keyword(s):  
Cycle Time ◽  
Semiconductor Manufacturing ◽  
Optimal Solution ◽  
Time Estimation ◽  
Pareto Optimal Solution ◽  
Experimental Results ◽  
Pareto Optimal ◽  
Cycle Times ◽  
Fuzzy Neural ◽  
Fluctuation Smoothing

A fuzzy-neural fluctuation smoothing rule is proposed in this study to improve the performance of scheduling jobs with various priorities in a semiconductor manufacturing factory. The fuzzy-neural fluctuation smoothing rule is modified from the well-known fluctuation smoothing rule by improving the accuracy of estimating the remaining cycle time of a job, which is done by applying Chen's fuzzy-neural approach with multiple buckets. To evaluate the effectiveness of the proposed methodology, production simulation is also applied in this study. According to experimental results, incorporating a more accurate remaining cycle time estimation mechanism did improve the scheduling performance especially in reducing the average cycle times. Besides, the fuzzy-neural fluctuation smoothing rule was also shown to be a Pareto optimal solution for scheduling jobs with various priorities in a semiconductor manufacturing factory.

Multiobjective scheduling for semiconductor manufacturing plants

2010 ◽  
Vol 34 (4) ◽  
pp. 555-566 ◽  
Author(s):  
O. Baez Senties ◽  
C. Azzaro-Pantel ◽  
L. Pibouleau ◽  
S. Domenech
Keyword(s):  
Semiconductor Manufacturing ◽  
Manufacturing Plants

Data Mining for Cycle Time Key Factor Identification and Prediction in Semiconductor Manufacturing

2009 ◽  
Vol 42 (4) ◽  
pp. 217-222
Author(s):  
Y. Meidan ◽  
B. Lerner ◽  
M. Hassoun ◽  
G. Rabinowitz
Keyword(s):  
Data Mining ◽  
Cycle Time ◽  
Semiconductor Manufacturing ◽  
Key Factor
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