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Frontiers of Engineering Management

ISSN 2095-7513

ISSN 2096-0255(Online)

CN 10-1205/N

Postal Subscription Code 80-905

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Front. Eng    2018, Vol. 5 Issue (4) : 507-514    https://doi.org/10.15302/J-FEM-2018045
RESEARCH ARTICLE
Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing time
Juan LIU, Fei QIAO(), Yumin MA, Weichang KONG
College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
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Abstract

The NP-hard scheduling problems of semiconductor manufacturing systems (SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme is refreshed in response to real-time uncertainties. The scheduling scheme is overly sensitive to the emergence of uncertainties because the optimization of performance (such as minimum make-span) and the system robustness cannot be achieved simultaneously by conventional reactive scheduling methods. To improve the robustness of the scheduling scheme, we propose a novel slack-based robust scheduling rule (SR) based on the analysis of robustness measurement for SMS with uncertain processing time. The decision in the SR is made in real time given the robustness. The proposed SR is verified under different scenarios, and the results are compared with the existing heuristic rules. Simulation results show that the proposed SR can effectively improve the robustness of the scheduling scheme with a slight performance loss.
Keywords semiconductor manufacturing system      uncertain processing time      dynamic scheduling      slack-based robust scheduling rule     
Corresponding Author(s): Fei QIAO   
Just Accepted Date: 22 August 2018   Online First Date: 22 October 2018    Issue Date: 29 November 2018
 Cite this article:   
Juan LIU,Fei QIAO,Yumin MA, et al. Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing time[J]. Front. Eng, 2018, 5(4): 507-514.
 URL:  
https://academic.hep.com.cn/fem/EN/10.15302/J-FEM-2018045
https://academic.hep.com.cn/fem/EN/Y2018/V5/I4/507
Fig.1  Scenario-based method
Job Operation (Processing time)
Machine 1 Machine 2 Machine 3 Machine 4
Job 1 O1,1(6) O1,2(6) O1,3(7) O1,4(5)
Job 2 O2,2(4) O2,3(4) O2,4(5) O2,1(4)
Job 3 O3,3(3) O3,1(3) O3,4(5) O3,2(9)
Job 4 O4,4(6) O4,2(6) O4,1(5) O4,3(5)
Tab.1  Example of four jobs and four machines
Fig.2  Example of the slack-based robust measure
Fig.3  Flowchart of the proposed SR
Fig.4  Gantt chart of the scheduling scheme applying SR
Scheduling scheme RM2 RM3 Makespan
Existing one 33 3.56 32
SR 34 4.13 34
Tab.2  Robustness measures and makespan of the example applying SR
Fig.5  Production flow of MiniFab model
SR CT ODR MOV
RM1 Min Max Avg RM1 Min Max Avg RM1 Min Max Avg
SR1 0.0016 90.95 124.49 106.44 0.0016 91.71% 92.41% 92.04% 0.0001 5024 5116 5062
SR2 0.0024 44.65 45.58 45.07 0.0012 91.60% 92.16% 91.86% 0.0012 5056 5172 5116
SR3 0.0024 44.65 45.58 45.07 0.0004 90.57% 91.25% 90.98% 0.0011 5057 5174 5117
EDD 0.0025 44.65 45.58 45.08 0.0016 91.69% 92.60% 92.04% 0.0016 5024 5190 5127
SRPT 0.0029 44.54 45.58 45.08 0.002 90.73% 91.82% 91.31% 0.0013 5057 5172 5116
CR 0.005 92.92 124.14 107.37 0.0067 90.50% 91.70% 91.32% 0.0042 4946 5152 5060
Tab.3  Robustness and performance measure of SR and other heuristic rules
Fig.6  Robustness and performance measure of SR and other heuristic rules in terms of CT
Fig.7  Robustness and performance measure of SR and other heuristic rules in terms of ODR
Fig.8  Robustness and performance measure of SR and other heuristic rules in terms of MOV
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