Monitoring process mean using generally weighted moving average chart for exponentially distributed characteristics
SCIE
SCOPUS
- Title
- Monitoring process mean using generally weighted moving average chart for exponentially distributed characteristics
- Authors
- Aslam, M.; Al-Marshadi, A.H.; Jun, Chi-Hyuck
- Date Issued
- 2017-01
- Publisher
- Taylor and Francis Inc.
- Abstract
- In this article, we will present a control chart using normal transformation and generally weighted moving average (GWMA) statistic when the quality characteristic follows the exponential distribution. We will develop the necessary measures to monitor the mean of the process using GWMA statistic and analyze the performance using simulation. The average run lengths for monitoring process average are given for various process shifts. The performance of the proposed chart is examined and compared with the existing control chart. The proposed control chart is effective for the monitoring of small shifts in the mean process. The application of the proposed chart is illustrated with the help of simulated data. ? 2017 Taylor & Francis Group, LLC.
- Keywords
- Control charts; Flowcharting; Process monitoring; Robustness (control systems); Statistical process control; Average run lengths; Distributed characteristics; Exponential distributions; Generally weighted moving average(GWMA); Normal transformation; Quality characteristic; simulation; Weighted moving averages; Quality control
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/50731
- DOI
- 10.1080/03610918.2015.1102936
- ISSN
- 0361-0918
- Article Type
- Article
- Citation
- Communications in Statistics: Simulation and Computation, vol. 46, no. 5, page. 3712 - 3722, 2017-01
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