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Test-sequence optimisation by survival analysis. (English) Zbl 07061308

Summary: Testing is an indispensable process for ensuring product quality in production systems. Reducing the time and cost spent on testing whilst minimising the risk of not detecting faults is an essential problem of process engineering. The optimisation of complex testing processes consisting of independent test steps is considered. Survival analysis-based models of an elementary test to efficiently combine the time-dependent outcome of the tests and costs related to the operation of the testing system were developed. A mixed integer non-linear programming (MINLP) model to formalize how the total cost of testing depends on the sequence and the parameters of the elementary test steps was proposed. To provide an efficient formalization of the scheduling problem and avoid difficulties due to the relaxation of the integer variables, the MINLP model as a P-graph representation-based process network synthesis problem was considered. The applicability of the methodology is demonstrated by a realistic case study taken from the computer manufacturing industry. With the application of the optimal test times and sequence provided by the SCIP (Solving Constraint Integer Programs) solver, \(0.1-5\%\) of the cost of the testing can be saved.

MSC:

90Bxx Operations research and management science
06A06 Partial orders, general
11B99 Sequences and sets
60G25 Prediction theory (aspects of stochastic processes)
62E17 Approximations to statistical distributions (nonasymptotic)
62G30 Order statistics; empirical distribution functions
62N02 Estimation in survival analysis and censored data
90C27 Combinatorial optimization
90C39 Dynamic programming

Software:

SCIP; NEOS
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References:

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