The Performance of Control Charts in the Presence of Assignable Causes
Moya-Fernández P. J.1, Álvarez E.2, Skalská H3
1Moya Fernández P.J ., Department of Quantitative Methods in Economics and Business, University of Granada, Granada, Spain.
2Álvarez E.., Department of Quantitative Methods in Economics and Business, University of Granada, Granada, Spain.
3Skalská Hana, Department of Informatics and Quantitative Methods, University of Hradec Králové, Hradec Králové, Czech Republic.
Manuscript received on 13 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 458-463 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2401037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The main objective of control charts is to evaluate the quality of a production process. A process is stable or in-control when the variability of the production process is only produced by common causes. However, it is said that the process is out-of-control if its variability is produced by assignable causes. An advantage of control charts is the detection and identification of assignable causes within the production process. The aim of this article is to analyse the performance of control charts under simulated (therefore known) changing conditions. Monte Carlo simulation studies are carried out to analyze the empirical performance of control charts under different scenarios. In particular, we first consider that the processes have a correct operation. Second, we consider processes that operate with quality characteristics that do not satisfy the required assumptions, and this issue may have an impact on the proportion of non-conforming articles. Third, we consider processes that suffer from a change on the performance of the production volume. The proposed studies allow to estimate an impact of the analyzed scenarios on the performance of control charts
Keywords: Control limits, simulation study, statistical process control, variance
Scope of the Article: Robotics and Control