Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters

In usual quality control methods, the quality of a process or product is evaluated by monitoring one or more quality characteristics using their corresponding distributions. However, when the quality characteristic is defined through the relationship between one or more response and independent variables, the regime is referred to as profiles monitoring. In this article, we improve the performance of the Exponentially Weighted Moving Average Range (EWMAR) control charts, which are implemented for monitoring linear profiles (i.e., intercept, slope and average residual between sample and reference lines) by integrating them with run rules in order to quickly detect various magnitudes of shifts in profile parameters. The validation of the proposed control chart is accomplished by examining its performance using the average run length (ARL) criteria. The proposed EWMAR chart with run rules exhibits a much better performance in detecting small and decreasing shifts than the other competing charts. Finally, an example from multivariate manufacturing industry is employed to illustrate the superiority of the EWMAR chart with run rules.

[1]  Rassoul Noorossana,et al.  Phase II monitoring of multivariate simple linear profiles , 2010, Comput. Ind. Eng..

[2]  A. Haq.  Adaptive MEWMA charts for univariate and multivariate simple linear profiles , 2020, Communications in Statistics - Theory and Methods.

[3]  Muhammad Riaz,et al.  On the Performance of Linear Profile Methodologies Under Runs Rules Schemes , 2015, Qual. Reliab. Eng. Int..

[4]  Muhammad Riaz,et al.  Improving the performance of CUSUM charts , 2011, Qual. Reliab. Eng. Int..

[5]  Qiang Zhou,et al.  Modeling multivariate profiles using Gaussian process-controlled B-splines , 2020, IISE Trans..

[6]  Seyed Taghi Akhavan Niaki,et al.  Economic-statistical design of simple linear profiles with variable sampling interval , 2016 .

[7]  Fugee Tsung,et al.  Monitoring General Linear Profiles Using Multivariate Exponentially Weighted Moving Average Schemes , 2007, Technometrics.

[8]  Mahmoud A. Mahmoud,et al.  Phase II Multiple Linear Regression Profile with Small Sample Sizes , 2015, Qual. Reliab. Eng. Int..

[9]  Lan Kang,et al.  On-Line Monitoring When the Process Yields a Linear Profile , 2000 .

[10]  Massimo Pacella,et al.  Monitoring roundness profiles based on an unsupervised neural network algorithm , 2011, Comput. Ind. Eng..

[11]  Abbas Saghaei,et al.  A CUSUM-based method for monitoring simple linear profiles , 2009 .

[12]  Fugee Tsung,et al.  LASSO-based multivariate linear profile monitoring , 2012, Ann. Oper. Res..

[13]  Tahir Abbas,et al.  Efficient Phase II Monitoring Methods for Linear Profiles Under the Random Effect Model , 2019, IEEE Access.

[14]  Scott D. Grimshaw,et al.  Nonlinear Profile Monitoring for Oven-Temperature Data , 2016 .

[15]  Zhonghua Li,et al.  Control chart based on likelihood ratio for monitoring linear profiles , 2009, Comput. Stat. Data Anal..

[16]  Philippe Castagliola,et al.  An overview on recent profile monitoring papers (2008-2018) based on conceptual classification scheme , 2018, Comput. Ind. Eng..

[17]  Kim Phuc Tran,et al.  Run Rules median control charts for monitoring process mean in manufacturing , 2017, Qual. Reliab. Eng. Int..

[18]  Petros E. Maravelakis,et al.  Statistical Process Control using Shewhart Control Charts with Supplementary Runs Rules , 2007 .

[19]  Tahir Mahmood,et al.  Alternative methods for the simultaneous monitoring of simple linear profile parameters , 2018, The International Journal of Advanced Manufacturing Technology.

[20]  Alireza Shadman,et al.  Monitoring linear profiles using Artificial Neural Networks with run rules , 2020, Expert Syst. Appl..

[21]  Tahir Abbas,et al.  On monitoring of linear profiles using Bayesian methods , 2016, Comput. Ind. Eng..

[22]  Longcheen Huwang,et al.  Monitoring general linear profiles using simultaneous confidence sets schemes , 2014, Comput. Ind. Eng..

[23]  Saddam Akber Abbasi,et al.  Efficient CV Control Charts Based on Ranked Set Sampling , 2019, IEEE Access.

[24]  Fred Spiring,et al.  Introduction to Statistical Quality Control , 2007, Technometrics.

[25]  F. S. Stover,et al.  Statistical quality control applied to ion chromatography calibrations , 1998 .

[26]  Rassoul Noorossana,et al.  Phase II monitoring of multivariate multiple linear regression profiles , 2011, Qual. Reliab. Eng. Int..

[27]  Saddam Akber Abbasi,et al.  On improved monitoring of linear profiles under modified successive sampling , 2019, Qual. Reliab. Eng. Int..

[28]  Jionghua Jin,et al.  Automatic feature extraction of waveform signals for in-process diagnostic performance improvement , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[29]  Saddam Akber Abbasi,et al.  Linear profile monitoring using EWMA structure under ranked set schemes , 2017 .

[30]  Yang Zhang,et al.  Directed control charts for detecting the shape changes from linear profiles to quadratic profiles , 2014 .

[31]  Douglas C. Montgomery,et al.  Using Control Charts to Monitor Process and Product Quality Profiles , 2004 .

[32]  Rassoul Noorossana,et al.  A parameters reduction method for monitoring multiple linear regression profiles , 2012 .

[33]  Sai Wang,et al.  The Monitoring of Linear Profiles with a GLR Control Chart , 2012 .

[34]  Alireza Shadman,et al.  Monitoring of linear profiles using generalized likelihood ratio control chart with variable sampling interval , 2018, Qual. Reliab. Eng. Int..

[35]  Amirhossein Amiri,et al.  A novel run rules based MEWMA scheme for monitoring general linear profiles , 2020, Comput. Ind. Eng..

[36]  Ioannis S. Triantafyllou.  Simulation-Based Comparative Analysis of Nonparametric Control Charts with Runs-Type Rules , 2020 .

[37]  Seyedeh Zahra Hosseinifard,et al.  Application of artificial neural networks in linear profile monitoring , 2011, Expert Syst. Appl..

[38]  Zhonghua Li,et al.  Phase II monitoring of generalized linear profiles using weighted likelihood ratio charts , 2016, Comput. Ind. Eng..

[39]  Saddam Akber Abbasi,et al.  Bayesian Monitoring of Linear Profiles Using DEWMA Control Structures With Random $X$ , 2018, IEEE Access.

[40]  Mohamed Limam,et al.  On the Use of the K-Chart for Phase II Monitoring of Simple Linear Profiles , 2013 .

[41]  William H. Woodall,et al.  Current research on profile monitoring , 2007 .

[42]  Changliang Zou,et al.  An Area‐based Methodology for the Monitoring of General Linear Profiles , 2017, Qual. Reliab. Eng. Int..

[43]  Muhammad Abid,et al.  Improved linear profiling methods under classical and Bayesian setups: An application to chemical gas sensors , 2020 .

[44]  Muhammad Riaz,et al.  An Improved Control Chart for Monitoring Linear Profiles and its Application in Thermal Conductivity , 2020, IEEE Access.

[45]  Muhammad Riaz,et al.  Simultaneous monitoring of linear profile parameters under progressive setup , 2018, Comput. Ind. Eng..

[46]  Athanasios C. Rakitzis,et al.  Runs rules schemes for monitoring process variability , 2010 .

[47]  Nan Chen,et al.  Phase-II monitoring in multichannel profile observations , 2019 .

[48]  Zhonghua Li,et al.  An exponentially weighted moving average scheme with variable sampling intervals for monitoring linear profiles , 2010, Comput. Ind. Eng..

[49]  Mahmoud A. Mahmoud,et al.  On the Monitoring of Linear Profiles , 2003 .

[50]  Jye-Chyi Lu,et al.  Equipment fault detection using spatial signatures , 1997 .