A Review and Perspective on Control Charting with Image Data

References

• Anagnostopoulos, C.; Vergados, D.; Kayafas, E.; Loumos, V.; and Stassinopoulos, G. (2001). “A Computer Vision Approach for Textile Quality Control”. The Journal of Visualization and Computer Animation 12 (1), pp. 31–44.
   Google Scholar
• Armingol, J. M.; Otamendi, J.; De la Escalera, A.; Pastor, J. M.; and Rodriguez, F. J. (2003). “Statistical Pattern Modeling in Vision-Based Quality Control Systems”. Journal of Intelligent and Robotic Systems 37, pp. 321–336.
   Web of Science ®Google Scholar
• Arpaia, P.; Betta, G.; Langella, A.; and Sacco, E. (1999). “Measurement Process Control by Means of Algorithms Based on Digital Image Processing”. IEE Proceedings-Science Measurement and Technology 146, pp. 27–34.
   Google Scholar
• Bersimis, S.; Psarakis, S.; and Panaretos, J. (2007). “Multivariate Statistical Process Control Charts: An Overview”. Quality and Reliability Engineering International 23, pp. 517–543.
   Web of Science ®Google Scholar
• Bharati, M. H. and MacGregor, J. F. (1998). “Multivariate Image Analysis for Real-Time Process Monitoring and Control”. Industrial and Engineering Chemistry Research 37, pp. 4715–4724.
   Web of Science ®Google Scholar
• Bharati, M. H.; MacGregor, J. F.; and Tropper, W. (2003). “Softwood Lumber Grading through on-Line Multivariate Image Analysis Techniques”. Industrial and Engineering Chemistry Research 42, pp. 5345–5353.
   Web of Science ®Google Scholar
• Chiu, D.; Guillaud, M.; Cox, D.; Follen, M.; and MacAulay, C. (2004). “Quality Assurance System Using Statistical Process Control: An Implementation for Image Cytometry”. Cellular Oncology 26, pp. 101–117.
   PubMed Web of Science ®Google Scholar
• Colosimo, B. M.; Mammarella, F.; and Petro, S. (2010). “Quality Control of Manufactured Surfaces”. In Frontiers in Statistical Quality Control 9, H. J. Lenz, P.-Th. Wilrich, and W. Schmid, eds., pp. 55–70. Berlin, Germany: Physica-Verlag.
   Google Scholar
• Colosimo, B. M. and Pacella, M. (2011). “Analyzing the Effect of Process Parameters on the Shape of 3D Profiles”. Journal of Quality Technology, to appear.
   Google Scholar
• Deng, J. L.. (1989). “Introduction to Grey System Theory”. The Journal of Grey System 1, pp. 1–24.
   Google Scholar
• Elbasi, E.; Long, Z.; Mehrotra, K.; Mohan, C.; and Varshney, P. (2005). “Control Charts Approach for Scenario Recognition in Video Sequences”. Turkish Journal of Electrical Engineering and Computer Sciences 13, pp. 303–309.
   Google Scholar
• Facco, P.; Bezzo, F.; Romagnoli, J.A.; and Barolo, M. (2008). “Using Digital Images for Fast, Reliable, and Automatic Characterization of Surface Quality”. Workshop on Nanomaterials Production, Characterization and Industrial Applications. Milano, Italy.
   Google Scholar
• Friedman, D. J. and Albin, S. L. (1991). “Clustered Defects in IC Fabrication: Impact on Process Control Charts”. IEEE Transactions on Semiconductor Manufacturing 4, pp. 36–42.
   Web of Science ®Google Scholar
• Garland, S. W.; Lees, B.; and Stevenson, J. C. (1997). “DXA Longitudinal Quality Control: A Comparison of Inbuilt Quality Assurance, Visual Inspection, Multi-Rule Shewhart Charts and CUSUM Analysis”. Osteoporosis International 7, pp. 231–237.
   PubMed Web of Science ®Google Scholar
• Geladi, P. and Grahn, H. (1996). Multivariate Image Analysis. Chichester, New York: Wiley.
   Google Scholar
• Gonzalez, R. C. and Woods, R. E. (2007). Digital Image Processing. Upper Saddle River, N.J: Prentice Hall.
   Google Scholar
• Graham, K. J.; Krishnapisharody, K.; Irons, G. A.; and MacGregor, J. F. (2007). “Monitoring Ladle Eye Dynamics Using Multivariate Statistical Methods”. Proceedings of the Iron & Steel Technology Conference. Indianapolis, IN.
   Google Scholar
• Grahn, H. and Geladi, P. (2007). Techniques and Applications of Hyperspectral Image Analysis. Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Hansen, M. H.; Nair, V. N.; and Friedman, D. J. (1997). “Monitoring Wafer Map Data from Integrated Circuit Fabrication Processes for Spatially Clustered Defects”. Technometrics 39, pp. 241–253.
   Web of Science ®Google Scholar
• Haralick, R.; Dinstein, I.; and Shanmugam, K. (1973). “Textural Features for Image Classification”. IEEE Transactions on Systems, Man, and Cybernetics 3, pp. 610–621.
   Web of Science ®Google Scholar
• Horst, R. L. and Negin, M. (1992). “Vision System for High-Resolution Dimensional Measurements and on-Line Inspection: Web Process Application”. IEEE Transactions on Industrial Applications 28, pp. 993–997.
   Web of Science ®Google Scholar
• Jähne, B. (2005). Digital Image Processing. Springer: Berlin.
   Google Scholar
• Jiang, B. C. and Jiang, S. J. (1998). “Machine Vision Based Inspection of Oil Seals”. Journal of Manufacturing Systems 17, pp. 159–166.
   Web of Science ®Google Scholar
• Jiang, B. C.; Wang, C.-C.; and Liu, H.-C. (2005). “Liquid Crystal Display Surface Uniformity Defect Inspection Using Analysis of Variance and Exponentially Weighted Moving Average Techniques”. International Journal of Production Research 43, pp. 67–80.
   Web of Science ®Google Scholar
• Jiang, W.; Han, S. W.; Tsui, K-L.; and Woodall, W. H. (2010). “Spatiotemporal Surveillance in the Presence of Spatial Correlation”. Statistics in Medicine, to appear.
   Google Scholar
• Jun, C.-H.; Hong, Y.; Kim, S. Y.; Park, K.-S.; and Park, H. (1999). “A Simulation-Based Semiconductor Chip Yield Model Incorporating a New Defect Cluster Index”. Microelectronics Reliability 39, pp. 451–456.
   Web of Science ®Google Scholar
• Knight, A. C. and Williams, E. D. (1992). “An Evaluation of Cusum Analysis and Control Charts Applied to Quantitative Gamma-Camera Uniformity Parameters for Automated Quality Control”. European Journal of Nuclear Medicine and Molecular Imaging 19, pp. 125–130.
   Web of Science ®Google Scholar
• Kourti, T. (2005). “Application of Latent Variable Methods to Process Control and Multivariate Statistical Process Control in Industry”. International Journal of Adaptive Control and Signal Processing 19, pp. 213–246.
   Web of Science ®Google Scholar
• Kourti, T. (2006). “Process Analytical Technology Beyond Real-Time Analyzers: The Role of Multivariate Analysis”. Critical Reviews in Analytical Chemistry 36, pp. 257–278.
   Web of Science ®Google Scholar
• Lavangnananda, K. and Piyatumrong, A. (2005). “Image Processing Approach to Features Extraction in Classification of Control Chart Patterns”. Proceedings of the 2005 IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications, Espoo, Finland, pp. 85–90.
   Google Scholar
• Liang, Y.-T. and Chiou, Y.-C. (2008). “Vision-Based Automatic Tool Wear Monitoring System”. Proceedings of the 7th World Congress on Intelligent Control and Automation, Chongqing, China, pp. 6031–6035.
   Google Scholar
• Lin, H.-D. (2007a). “Automated Visual Inspection of Ripple Defects Using Wavelet Characteristic Based Multivariate Statistical Approach”. Image and Vision Computing 25, pp. 1785–1801.
   Web of Science ®Google Scholar
• Lin, H.-D. (2007b). “Computer-aided Visual Inspection of Surface Defects in Ceramic Capacitor Chips”. Journal of Materials Processing Technology 189, pp. 19–25.
   Web of Science ®Google Scholar
• Lin, H.-D.; Chung, C.-Y.; and Lin, W.-T. (2008). “Principal Component Analysis Based on Wavelet Characteristics Applied to Automated Surface Defect Inspection”. WSEAS Transactions on Computers 3, pp. 193–202.
   Google Scholar
• Lin, H.-D. and Chiu, S. (2006). “Computer-Aided Vision System for Mura-Type Defect Inspection in Liquid Crystal Displays”. Lecture Notes in Computer Science 4319, pp. 442–452.
   Google Scholar
• Lindquist, M. A.; Waugh, C.; and Wager, T. D. (2007). “Modeling State-Related fMRI Activity Using Change-Point Theory”. NeuroImage 35, pp. 1125–1141.
   PubMed Web of Science ®Google Scholar
• Liu, J.; MacGregor, J. F.; Duchesne, C.; and Bartolacci, G. (2005). “Flotation Froth Monitoring Using Multiresolutional Multivariate Image Analysis”. Minerals Engineering 18, pp. 65–76.
   Web of Science ®Google Scholar
• Liu, J. and MacGregor, J. F. (2006). “Estimation and Monitoring of Product Aesthetics: Application to Manufacturing of ‘Engineered Stone’ Countertops”. Machine Vision and Applications 16, pp. 374–383.
   Web of Science ®Google Scholar
• Liu, Z. Q.; Austin, T.; Thomas, C. D. L.; and Clement, J. G. (1996). “Bone Feature Analysis Using Image Processing Techniques”. Computers in Biology and Medicine 26, pp. 65–76.
   PubMed Web of Science ®Google Scholar
• Lu, C.-J. and Tsai, D.-M. (2005). “Automatic Defect Inspection for LCDs Using Singular Value Decomposition”. The International Journal of Advanced Manufacturing Technology 25, pp. 53–61.
   Web of Science ®Google Scholar
• Lu, Y.; Mathur, A. K.; Blunt, B. A.; Glüer, C. C.; Will, A. S.; Fuerst, T. P.; Jergas, M. D.; Andriano, K. N.; Cummings, S. R.; and Genant, H. K. (1996). “Dual X-Ray Absorptiometry Quality Control: Comparison of Visual Examination and Process-Control Charts”. Journal of Bone and Mineral Research 11 (5), pp. 626–637.
   PubMed Web of Science ®Google Scholar
• Lu, C.-J. and Tsai, D.-M. (2005). “Automatic Defect Inspection for LCDs using Singular Value Decomposition”. The International Journal of Advanced Manufacturing Technology 25 (1), pp. 53–61.
   Web of Science ®Google Scholar
• Lyu, J. and Chen, M. (2009). “Automated Visual Inspection Expert System for Multivariate Statistical Process Control Chart”. Expert Systems with Applications 36, pp. 5113–5118.
   Web of Science ®Google Scholar
• MacGregor, J. F.; Bharati, M. H.; and Yu, H. (2001). “Multivariate Image Analysis for Process Monitoring and Control”. In Process Imaging for Automatic Control, H. McCann and D. M. Scott, eds., pp. 17–26. Proceedings of SPIE, 4188.
   Google Scholar
• Malamas, E. N.; Petrakis, E. G.; Zervakis, M.; Petit, L.; and Legat, J.-D. (2003). “A Survey on Industrial Vision Systems, Applications and Tools”. Image and Vision Computing 21, pp. 171–188.
   Web of Science ®Google Scholar
• Mason, R. L.; Tracy, N. D.; and Young, J. C. (1997). “A Practical Approach for Interpreting Multivariate T2 Control Chart Signals”. Journal of Quality Technology 29, pp. 396–406.
   Web of Science ®Google Scholar
• Megahed, F. M. and Camelio, J. A. (2010a). “Real-Time Fault Detection in Manufacturing Environments Using Face Recognition Techniques”. Journal of Intelligent Manufacturing, to appear.
   Google Scholar
• Megahed, F. M.; Wells, L. J.; and Camelio, J. A. (2010b). “The Use of 3D Laser Scanners in Statistical Process Control”. SAE Conference on Aerospace Manufacturing and Automated Fastening Conference & Exhibition, Wichita, Kansas.
   Google Scholar
• Montgomery, D. C. (2008). Introduction to Statistical Quality Control, Sixth Edition. Hoboken, N.J.: John Wiley & Sons.
   Google Scholar
• Nalwa, V. S. (1993). A Guided Tour of Computer Vision. Reading, Mass.: Addison-Wesley.
   Google Scholar
• Nembhard, H. B.; Ferrier, N. J.; Osswald, T. A.; and Sanz-Uribe, J. R. (2003). “An Integrated Model for Statistical and Vision Monitoring in Manufacturing Transitions”. Quality and Reliability Engineering International 19, pp. 461–476.
   Web of Science ®Google Scholar
• Orwoll, E.; Oviatt, S.; and Biddle, J. (1993). “Precision of Dual-Energy X-Ray Absorptiometry: Development of Quality Control Rules and Their Application in Longitudinal Studies”. Journal of Bone and Mineral Research 8, pp. 693–699.
   PubMed Web of Science ®Google Scholar
• Pearson, D. and Cawte, S. A. (1997). “Long-Term Quality Control of DXA: A Comparison of Shewhart Rules and CUSUM Charts”. Osteoporosis International 7, pp. 338–343.
   PubMed Web of Science ®Google Scholar
• Pearson, D. and Lawson, N. (2007). “Laboratory and Instrument Quality Control”. In Clinical Trials in Osteoporosis, pp. 141–159. London: Springer.
   Google Scholar
• Pereira, A. C.; Reis, M. S.; and Saraiva, P. M. (2009). “Quality Control of Food Products Using Image Analysis and Multivariate Statistical Tools”. Industrial and Engineering Chemistry Research 48, pp. 988–998.
   Web of Science ®Google Scholar
• Rogerson, P. and Yamada, I. (2009). Statistical Detection and Surveillance of Geographic Clusters. Chapman & Hall/CRC: Boca Raton, FL.
   Google Scholar
• Schmitt, K. M.; Young, R. C. D.; Riddington, J. R.; Budgett, D. M.; and Chatwin, C. R. (2000). “Image Processing Applied to Brick Quality Control”. The International Journal of Advanced Manufacturing Technology 16, pp. 434–440.
   Web of Science ®Google Scholar
• Simmons, A.; Moore, E.; and Williams, S. (1999). “Quality Control for Functional Magnetic Resonance Imaging Using Automated Data Analysis and Shewhart Charting”. Magnetic Resonance in Medicine 41, pp. 1274–1278.
   PubMed Web of Science ®Google Scholar
• Sonesson, C. (2007). “A CUSUM Framework for Detection of Space-time Clusters Using Scan Statistics”. Statistics in Medicine 26, pp. 4770–4789.
   PubMed Web of Science ®Google Scholar
• Stöcker, T., Schneider, F., Klein, M., Habel, U., Kellerman, T., Zilles, K., and Shah, N. J. (2005). “Automated Quality Assurance Routines for fMRI Data Applied to a Multicenter Study”. Human Brain Mapping 25, pp. 237–246.
   PubMed Web of Science ®Google Scholar
• Styner, M.; Oguz, I.; Xu, S.; Pantazis, D.; and Gerig, G. (2007). “Statistical Group Differences in Anatomical Shape Analysis Using Hotelling T2 Metric”. Progress in Biomedical Optics and Imaging 8 (3).
   Google Scholar
• Tan, J.; Chang, Z.; and Hsieh, F. (1996). “Implementation of an Automated Real-Time Statistical Process Controller”. Journal of Food Process Engineering 19, pp. 49–61.
   Web of Science ®Google Scholar
• Taniguchi, K., Ueta, K., and Tatsumi, S. (2006). “A Mura Detection Method”. Pattern Recognition 39 (6), pp. 1044–1052.
   Web of Science ®Google Scholar
• Tong, L.-I.; Wang, C.-H.; and Huang, C.-L. (2005). “Monitoring Defects in IC Fabrication Using a Hotelling T2 Control Chart”. IEEE Transactions on Semiconductor Manufacturing 18, pp. 140–147.
   Web of Science ®Google Scholar
• Tunák, M. and Linka, A. (2008). “Directional Defects in Fabrics”. Research Journal of Textile and Apparel 12, pp. 13–22.
   Google Scholar
• Tunák, M.; Linka, A.; and Volf, P. (2009). “Automatic Assessing and Monitoring of Weaving Density”. Fibers and Polymers 10 (6), pp. 830–836.
   Web of Science ®Google Scholar
• Vihonen, J.; Jylha, J.; Ala-Kleemola, T.; Ruotsalainen, M.; Kauppila, J.; Huotilainen, T.; Rauhamaa, J.; and Visa, A. (2008). “Directional Filtering for Sequential Image Analysis”. IEEE Signal Processing Letters 15, pp. 902–905.
   Web of Science ®Google Scholar
• Wang, K. and Tsung, F. (2005). “Using Profile Monitoring Techniques for a Data-Rich Environment with Huge Sample Size”. Quality and Reliability Engineering International 21, pp. 677–688.
   Web of Science ®Google Scholar
• Western Electric Company (1956). Statistical Quality Control Handbook. Indianapolis, IN.
   Google Scholar
• Wheeler, D. J. and Chambers, D. S. (1992). Understanding Statistical Process Control. Knoxville, TN: SPC Press.
   Google Scholar
• Woodall, W. H. (2000). “Controversies and Contradictions in Statistical Process Control”. Journal of Quality Technology 32, pp. 341–350.
   Web of Science ®Google Scholar
• Woodall, W. H. (2007). “Current Research on Profile Monitoring”. Produçαo 17, pp. 420–425.
   Google Scholar
• Woodall, W. H.; Spitzner, D. J.; Montgomery, D. C.; and Gupta, S. (2004). “Using Control Charts to Monitor Process and Product Quality Profiles”. Journal of Quality Technology 36, pp. 309–320.
   Web of Science ®Google Scholar
• Woodall, W. H. and Adams, B. M. (1998). Statistical Process Control. Chapter 7 in Handbook of Statistical Methods for Engineers and Scientists. Second Edition, H. M. Wadsworth ed. New York: McGraw-Hill.
   Google Scholar
• Yu, H. and MacGregor, J. F. (2004). “Monitoring Flames in an Industrial Boiler Using Multivariate Image Analysis”. AIChE Journal 50, pp. 1474–1483.
   Web of Science ®Google Scholar
• Yu, H.; MacGregor, J. F.; Haarsma, G.; and Bourg, W. (2003). “Digital Imaging for Online Monitoring and Control of Industrial Snack Food Processes”. Industrial and Engineering Chemistry Research 42, pp. 3036–3044.
   Web of Science ®Google Scholar
• Zuech, N. (2000). Understanding and Applying Machine Vision. New York: Marcel Dekker.
   Google Scholar