This paper presents an optimization analysis of a queuing system for a particular post office as a tool to increase system reliability. The consideration of system reliability in terms of queuing system failures is very relevant. One way to increase reliability is to analyse the system and its parameters in order to identify its most critical flaws. We used the chi-squared goodness-of-fit test based on the validation of a null hypothesis over an alternative hypothesis. The purpose of the test was to verify the correspondence of the measured data with a theoretical probability distribution. Measurements of relevant data were performed on the specific post office that represented the subject of our research. This approach proved to be a powerful tool in system analysis and optimization. The results of such an analysis can serve as the basis for the modelling of queuing systems.


    Access

    Download


    Export, share and cite



    Title :

    RELIABILITY ENHANCEMENT USING OPTIMIZATION ANALYSIS


    Contributors:


    Publication date :

    2018




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Reliability-Based Design Optimization Using Efficient Global Reliability Analysis

    Bichon, B. / Mahadevan, S. / Eldred, M. | British Library Conference Proceedings | 2009


    Reliability-Based Design Optimization Using Efficient Global Reliability Analysis

    Bichon, Barron / Mahadevan, Sankaran / Eldred, Michael | AIAA | 2009


    Enhancement of Process/Product Performance Through Reliability Analysis

    Mohammed, M. H. / IEEE; Dayton Section / IEEE; Aerospace and Electronics Systems Society | British Library Conference Proceedings | 1996


    Reliability Enhancement Methodology and Modelling

    Marshall, J. / Jones, J. / Confederation of European Aerospace Societies | British Library Conference Proceedings | 2001


    Structural design optimization based on reliability analysis using evidence theory

    Bae,H.R. / Grandhi,R.V. / Canfiel,R.A. et al. | Automotive engineering | 2003