Development of fuzzy logic-based statistical process control chart pattern recognition system

This study developed a fuzzy logic system for online variation detection by recognizing patterns in statistical process control (SPC) charts. The system enables quality engineers to take corrective actions for an out-of-control manufacturing process. The fuzzy logic SPC system has three subsystems and is able to detect most common four patterns. Data go through subsystems in the absence of detective patterns. Otherwise, data will be eliminated when a particular pattern is recognized on the SPC chart. The user-friendly output interface reduces human analysis errors. The performance of the developed fuzzy logic system is tested by a simulated process.

[1]  Joseph C. Chen,et al.  A fuzzy logic based approach for pokayoke stoplight control in unmanned manufacturing cells , 1996 .

[2]  Francesco Masulli,et al.  On the structure of a neuro-fuzzy system to forecast chaotic time series , 1996, 1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report.

[3]  Shankar Chakraborty,et al.  An expert system for control chart pattern recognition , 2012 .

[4]  J. D. T. Tannock,et al.  A neural network approach to characterize pattern parameters in process control charts , 1999, J. Intell. Manuf..

[5]  Tawfik T. El-Midany,et al.  A proposed framework for control chart pattern recognition in multivariate process using artificial neural networks , 2010, Expert Syst. Appl..

[6]  Mohammad Hossein Fazel Zarandi,et al.  A hybrid fuzzy adaptive sampling - Run rules for Shewhart control charts , 2008, Inf. Sci..

[7]  Fu-Kwun Wang,et al.  Using adaptive network-based fuzzy inference system to forecast automobile sales , 2011, Expert Syst. Appl..

[8]  James R. Evans,et al.  A framework for expert system development in statistical quality control , 1988 .

[9]  Kudret Demirli,et al.  Fuzzy logic based assignable cause diagnosis using control chart patterns , 2010, Inf. Sci..

[10]  Joseph C. Chen,et al.  Development of a fuzzy-nets-based surface roughness prediction system in turning operations , 2007, Comput. Ind. Eng..

[11]  J. Rene Villalobos,et al.  Using fixed and adaptive multivariate SPC charts for online SMD assembly monitoring , 2005 .

[12]  Suresh Chand,et al.  Estimating the limits for statistical process control charts: A direct method improving upon the bootstrap , 2007, Eur. J. Oper. Res..

[13]  John F. MacGregor,et al.  Multivariate SPC charts for monitoring batch processes , 1995 .

[14]  Chuen-Sheng Cheng,et al.  A NEURAL NETWORK APPROACH FOR THE ANALYSIS OF CONTROL CHART PATTERNS , 1997 .

[15]  Joseph C. Chen,et al.  Development of a fuzzy-nets-based in-process surface roughness adaptive control system in turning operations , 2006, Expert Syst. Appl..

[16]  Duc Truong Pham,et al.  An Integrated Neural Network and Expert System Tool for Statistical Process Control , 1995 .

[17]  Serhat Kucukali,et al.  Turkey’s short-term gross annual electricity demand forecast by fuzzy logic approach , 2010 .

[18]  Joseph C. Chen,et al.  Fuzzy neural network-based in-process mixed material-caused flash prediction (FNN-IPMFP) in injection molding operations , 2006 .

[19]  Bart Kosko,et al.  Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence , 1991 .

[20]  Rod C. Scott,et al.  Statistical Process Control (SPC)—A simple objective method for monitoring seizure frequency and evaluating effectiveness of drug interventions in refractory childhood epilepsy , 2010, Epilepsy Research.

[21]  Layth C. Alwan.  Effects of autocorrelation on control chart performance , 1992 .

[22]  Zyed Zalila,et al.  Fuzzy supervision in statistical process control , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[23]  C. Morgan,et al.  Multiple retailer supplier performance: An exploratory investigation into using SPC techniques , 2008 .

[24]  James Tannock,et al.  A fuzzy control charting method for individuals , 2003 .

[25]  Chuen-Chien Lee.  FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[26]  H. Rowlands,et al.  A fuzzy logic application in SPC evaluation and control , 1999, 1999 7th IEEE International Conference on Emerging Technologies and Factory Automation. Proceedings ETFA '99 (Cat. No.99TH8467).

[27]  K. Srikaeo,et al.  The use of statistical process control (SPC) to enhance the validation of critical control points (CCPs) in shell egg washing , 2002 .

[28]  Norman P. Bresky,et al.  Tools and Methods for the Improvement of Quality , 1990 .

[29]  Li-Xin Wang.  Stable adaptive fuzzy control of nonlinear systems , 1993, IEEE Trans. Fuzzy Syst..

[30]  Jen Tang,et al.  Control Charts for Dependent and Independent Measurements Based on Bootstrap Methods , 1996 .

[31]  R. Plante,et al.  Statistical Process Control via the Subgroup Bootstrap , 1995 .

[32]  Jakob Edo Wieringa.  Statistical process control for serially correlated data , 1999 .

[33]  Chung-Tsen Tsao,et al.  Fuzzy net present values for capital investments in an uncertain environment , 2012, Comput. Oper. Res..

[34]  Larry Weinstein,et al.  Which Control Chart Should You Use , 2006 .

[35]  T. Yamakawa.  Stablization of an inverted pendulum by a high-speed fuzzy logic controller hardware system , 1989 .