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Simulation Modeling and Analysis of Fire Fighting Operations in the State of Kuwait

Simulation Modeling and Analysis of Fire Fighting Operations in the State of Kuwait

Mehmet Savsar, Esra Aleisa
Copyright: © 2015 |Volume: 8 |Issue: 2 |Pages: 18
ISSN: 1935-5726|EISSN: 1935-5734|EISBN13: 9781466676404|DOI: 10.4018/IJISSCM.2015040103
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MLA

Savsar, Mehmet, and Esra Aleisa. "Simulation Modeling and Analysis of Fire Fighting Operations in the State of Kuwait." IJISSCM vol.8, no.2 2015: pp.31-48. http://doi.org/10.4018/IJISSCM.2015040103

APA

Savsar, M. & Aleisa, E. (2015). Simulation Modeling and Analysis of Fire Fighting Operations in the State of Kuwait. International Journal of Information Systems and Supply Chain Management (IJISSCM), 8(2), 31-48. http://doi.org/10.4018/IJISSCM.2015040103

Chicago

Savsar, Mehmet, and Esra Aleisa. "Simulation Modeling and Analysis of Fire Fighting Operations in the State of Kuwait," International Journal of Information Systems and Supply Chain Management (IJISSCM) 8, no.2: 31-48. http://doi.org/10.4018/IJISSCM.2015040103

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Abstract

Emergency services, including firefighting operations, are complex processes and involve several activities in different stages that function together to achieve a main goal of preventing destruction in human life, property, and environment. This study uses discrete event simulation (DES) to model and improve firefighting operations in the state of Kuwait. The main objective is to reduce the response time required to reach an accident place. It is a life-saving criterion that needs to be considered. This study is conducted by collecting thorough data of fire operation department over a period of five years and accordingly creating a valid simulation model to analyse the system under current operational conditions nationwide. Analysis of variance (ANOVA) was used to identify factors that were statistically proven to have positive effects in reducing response time. A simulation model was used as a medium to carry out these experiments. The results of simulation model were validated at 95% confidence level. The effectiveness of the analysis is examined by incorporating related parameters from the ANOVA model into simulation model. The response time was reduced from seven minutes to three minutes on average per incident per fire station.

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