Screening for important factors in large-scale simulation models: some industrial experiments
2015 (English)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE credits
Student thesis
Abstract [en]
The present project discusses the application of screening techniques in large-scale simulation models with the purpose of determining whether this kind of procedures could be a substitute for or a complement to simulation-based optimization for bottleneck identification and improvement.
Based on sensitivity analysis, the screening techniques consist in finding the most important factors in simulation models where there are many factors, in which presumably only a few or some of these factors are important. The screening technique selected to be studied in this project is Sequential Bifurcation. This method consists in grouping the potentially important factors, dividing the groups continuously depending on the response generated from the model of the system under study.
The results confirm that the application of the Sequential Bifurcation method can considerably reduce the simulation time because of the number of simulations needed, which decreased compared with the optimization study. Furthermore, by introducing two-factor interactions in the metamodel, the results are more accurate and may even be as accurate as the results from optimization. On the other hand, it has been found that the application of Sequential Bifurcation could become a problem in terms of accuracy when there are many storage buffers in the decision variables list.
Due to all of these reasons, the screening techniques cannot be a complete alternative to simulation-based optimization. However, as shown in some initial results, the combination of these two methods could yield a promising roadmap for future research, which is highly recommended by the authors of this project.
Place, publisher, year, edition, pages
2015. , p. 100
Keywords [en]
Sequential Bifurcation, Screening, Design of experiments, Optimization, Discrete Event Simulation, Simulation
Keywords [es]
Optimización, Simulación de Eventos Discretos, Simulación, Diseño de experimentos, Organización Industrial, Ingeniería Industrial
National Category
Other Engineering and Technologies not elsewhere specified
Identifiers
URN: urn:nbn:se:his:diva-11484OAI: oai:DiVA.org:his-11484DiVA, id: diva2:850911
Subject / course
Automation Engineering
Educational program
Industrial Automation Engineer
Presentation
2015-06-03, 08:08 (English)
Supervisors
Examiners
2015-10-022015-09-022015-10-02Bibliographically approved