| 1 | Error Detection and Pattern Prediction Through Phase II Process Monitoring显示文摘The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution.It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement.The current study introduces control charts that help the manufacturing concerns to keep the production process in control.It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance.The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts.The findings suggest that an extended exponentially weighted moving average control chart based on the percentiles estimator performs better than exponentially weightedmoving average control charts based on the percentiles estimator and modified maximum likelihood estimator.Further,these results will help the firms in the early detection of errors that enhance the process reliability of the telecommunications and financing industry. | Azam Zaka Riffat Jabeen Kanwal Iqbal Khan | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 2 | Control Charts for the Shape Parameter of Power Function Distribution under Different Classical Estimators显示文摘In practice,the control charts for monitoring of process mean are based on the normality assumption.But the performance of the control charts is seriously affected if the process of quality characteristics departs from normality.For such situations,we have modified the already existing control charts such as Shewhart control chart,exponentially weighted moving average(EWMA)control chart and hybrid exponentially weighted moving average(HEWMA)control chart by assuming that the distribution of underlying process follows Power function distribution(PFD).By considering the situation that the parameters of PFD are unknown,we estimate them by using three classical estimation methods,i.e.,percentile estimator(P.E),maximum likelihood estimator(MLE)and modified maximum likelihood estimator(MMLE).We construct Shewhart,EWMA and HEWMA control charts based on P.E,MLE and MMLE.We have compared all these control charts using Monte Carlo simulation studies and concluded that HEWMA control chart under MLE is more sensitive to detect an early shift in the shape parameter when the distribution of the underlying process follows power function distribution. | Azam Zaka Ahmad Saeed Akhter Riffat Jabeen Aamir Sanaullah | 2021 | Computer Modeling in Engineering & Sciences2021，，6： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员