Hierarchical Test Sequencing for Complex Systems

Testing complex systems, such as the ASML TWINSCAN lithographic machine, is expensive and time consuming. In a previous work, a test sequencing method to calculate time-optimal test sequences has been developed. Because complex systems are composed of several subsystems, which are again composed of...

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Bibliographic Details
Published in:IEEE transactions on systems, man and cybernetics. Part A, Systems and humans man and cybernetics. Part A, Systems and humans, 2009-05, Vol.39 (3), p.640-649
Main Authors: Boumen, R., Ruan, S., de Jong, I., van de Mortel-Fronczak, J.M., Rooda, J.E., Pattipati, K.R.
Format: Article
Language:English
Subjects:
Algorithms
Complex systems
Cybernetics
Heuristic
Hierarchical systems
Hierarchical test sequencing
Human
Industrial relations
Knowledge engineering
Manufacturing industries
Manufacturing systems
Mathematical models
Mechanical engineering
Modules
Optimization
Semiconductor device manufacture
Semiconductor device testing
semiconductor manufacturing industry
Sequencing
System testing
Tangram
test strategy
Time to market
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Summary:Testing complex systems, such as the ASML TWINSCAN lithographic machine, is expensive and time consuming. In a previous work, a test sequencing method to calculate time-optimal test sequences has been developed. Because complex systems are composed of several subsystems, which are again composed of several modules, there exists a need to hierarchically model test sequencing problems. Such a hierarchical test sequencing problem consists of a high-level model that describes a test sequencing problem at the system level, and one or more low-level models that describe the test sequencing problems at the subsystem or module level. The tests at the system level correspond to the solutions of low-level problems. This paper describes a hierarchical test sequencing model and proposes two algorithms to compute an optimal test sequence. The benefits of hierarchically modeling a problem are less computational effort and less modeling effort, because not all relations are needed. This is illustrated by a small example. The industrial relevance of this method is illustrated on a case study related to a manufacturing testing phase of a lithographic machine.
ISSN:1083-4427
2168-2216
1558-2426
2168-2232
DOI:10.1109/TSMCA.2009.2014550