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Cost Analysis of Poor Quality Using a Software Simulation

Author

Listed:
  • Jana Fabianová

    (Technical University of Košice, Košice, Slovakia)

  • Jaroslava Janeková

    (Technical University of Košice, Košice, Slovakia)

  • Daniela Onofrejová

    (Technical University of Košice, Košice, Slovakia)

Abstract

The issues of quality, cost of poor quality and factors affecting quality are crucial to maintaining a competitiveness regarding to business activities. Use of software applications and computer simulation enables more effective quality management. Simulation tools offer incorporating the variability of more variables in experiments and evaluating their common impact on the final output. The article presents a case study focused on the possibility of using computer simulation Monte Carlo in the field of quality management. Two approaches for determining the cost of poor quality are introduced here. One from retrospective scope of view, where the cost of poor quality and production process are calculated based on historical data. The second approach uses the probabilistic characteristics of the input variables by means of simulation, and reflects as a perspective view of the costs of poor quality. Simulation output in the form of a tornado and sensitivity charts complement the risk analysis.

Suggested Citation

  • Jana Fabianová & Jaroslava Janeková & Daniela Onofrejová, 2017. "Cost Analysis of Poor Quality Using a Software Simulation," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(44), pages 181-181, February.
    • Handle: RePEc:aes:amfeco:v:s10:y:2017:i:18:p:181
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    References listed on IDEAS

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    1. Arumugam, V. & Antony, Jiju & Kumar, Maneesh, 2013. "Linking learning and knowledge creation to project success in Six Sigma projects: An empirical investigation," International Journal of Production Economics, Elsevier, vol. 141(1), pages 388-402.
    2. Arumugam, V. & Antony, Jiju & Linderman, Kevin, 2016. "The influence of challenging goals and structured method on Six Sigma project performance: A mediated moderation analysis," European Journal of Operational Research, Elsevier, vol. 254(1), pages 202-213.
    3. Hsu, Ya-Chen & Pearn, W.L. & Wu, Pei-Ching, 2008. "Capability adjustment for gamma processes with mean shift consideration in implementing Six Sigma program," European Journal of Operational Research, Elsevier, vol. 191(2), pages 517-529, December.
    4. Nourelfath, Mustapha & Hassan, Jawad, 2015. "Six Sigma performance for non-normal processesAuthor-Name: Aldowaisan, Tariq," European Journal of Operational Research, Elsevier, vol. 247(3), pages 968-977.
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    More about this item

    Keywords

    poor quality cost analysis; Monte Carlo simulation;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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