Exploratory image data analysis for quality improvement hypothesis generation

References

• Abbasi, S. A. 2010. On the performance of the EWMA chart in the presence of two-component measurement error. Quality Engineering 22 (3):199–213. doi: 10.1080/08982111003785649.
   Web of Science ®Google Scholar
• Ahonen, T., A. Hadid, and M. Pietikainen. 2006. Face description with local binary patterns: Application to face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 28 (12):2037–41. doi: 10.1109/tpami.2006.244.
   PubMed Web of Science ®Google Scholar
• Allen, T. T. 2019. Introduction to engineering statistics and lean six sigma: Statistical quality control and design of experiments and systems, vol. 3. London: Springer.
   Google Scholar
• Allen, T. T., Z. Sui, and K. Akbari. 2018. Exploratory text data analysis for quality hypothesis generation. Quality Engineering 30 (4):701–12. doi: 10.1080/08982112.2018.1481216.
   Web of Science ®Google Scholar
• Allen, T. T., H. Xiong, and S.-H. Tseng. 2020. Expert refined topic models to edit topic clusters in image analysis applied to welding engineering. Informatics 7 (3):21. doi: 10.3390/informatics7030021.
   Google Scholar
• Bisgaard, S. 1996. The importance of graphics in problem solving and detective work. Quality Engineering 9 (1):157–62. doi: 10.1080/08982119608919028.
   Google Scholar
• Blei, D. M., A. Y. Ng, and M. I. Jordan. 2003. Latent Dirichlet allocation. Journal of Machine Learning Research 3:993–1022. doi: 10.1162/jmlr.2003.3.4-5.993.
   Web of Science ®Google Scholar
• Canny, J. 1986. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8 (6):679–98. doi: 10.1109/TPAMI.1986.4767851.
   Web of Science ®Google Scholar
• Chang, S. I., and J. S. Ravathur. 2005. Computer vision based non-contact surface roughness assessment using wavelet transform and response surface methodology. Quality Engineering 17 (3):435–51. doi: 10.1081/QEN-200059881.
   Google Scholar
• Chen, J., S. Shan, C. He, G. Zhao, M. Pietikäinen, X. Chen, and W. Gao. 2009. WLD: A robust local image descriptor. IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (9):1705–20. doi: 10.1109/tpami.2009.155.
   Web of Science ®Google Scholar
• De Mast, J., and M. Bergman. 2006. Hypothesis generation in quality improvement projects: Approaches for exploratory studies. Quality and Reliability Engineering International 22 (7):839–50. doi: 10.1002/qre.767.
   Web of Science ®Google Scholar
• De Mast, J., S. H. Steiner, W. P. Nuijten, and D. Kapitan. 2023. Analytical problem solving based on causal, correlational and deductive models. The American Statistician 77 (1):51–61. doi: 10.1080/00031305.2021.2023633.
   Web of Science ®Google Scholar
• De Mast, J., and A. Trip. 2007. Exploratory data analysis in quality-improvement projects. Journal of Quality Technology 39 (4):301–11. doi: 10.1080/00224065.2007.11917697.
   Web of Science ®Google Scholar
• Ghorai, S., A. Mukherjee, M. Gangadaran, and P. K. Dutta. 2013. Automatic defect detection on hot-rolled flat steel products. IEEE Transactions on Instrumentation and Measurement 62 (3):612–21. doi: 10.1109/TIM.2012.2218677.
   Web of Science ®Google Scholar
• Gonzalez, R. C., and R. E. Woods. 2018. Digital image processing. 4th ed. Bangalore, India: Pearson Education.
   Google Scholar
• Good, I. J. 1983. The philosophy of exploratory data analysis. Philosophy of Science 50 (2):283–95. doi: 10.1086/289110.
   Web of Science ®Google Scholar
• Griffiths, T. L., and M. Steyvers. 2004. Finding scientific topics. Proceedings of the National Academy of Sciences of the United States of America 101 (Suppl 1):5228–35. doi: 10.1073/pnas.0307752101.
   PubMed Web of Science ®Google Scholar
• Harris, C., and M. Stephens. 1998. A combined corner and edge detector. Paper presented at the Proceedings of 4th Alvey Vision Conference, Manchester, UK, August 31–September 2.
   Google Scholar
• Hoaglin, D. C., F. Mosteller, and J. W. Tukey. 1983. Understanding robust and exploratory data analysis. New York, NY: Wiley.
   Google Scholar
• Lawson, J. 2019. Phase II monitoring of variability using Cusum and EWMA charts with individual observations. Quality Engineering 31 (3):417–29. doi: 10.1080/08982112.2018.1557205.
   Web of Science ®Google Scholar
• Lepenioti, K., A. Bousdekis, D. Apostolou, and G. Mentzas. 2020. Prescriptive analytics: Literature review and research challenges. International Journal of Information Management 50:57–70. doi: 10.1016/j.ijinfomgt.2019.04.003.
   Web of Science ®Google Scholar
• Lucas, J. M., and M. S. Saccucci. 1990. Exponentially weighted moving average control schemes: Properties and enhancements. Technometrics 32 (1):1–12. doi: 10.1080/00401706.1990.10484583.
   Web of Science ®Google Scholar
• Nederbragt, A. J., P. Francus, J. Bollmann, and M. J. Soreghan. 2005. Image calibration, filtering, and processing. In Image analysis, sediments and paleoenvironments, ed. P. Francus, 35–58. Dordrecht: Springer. doi: 10.1007/1-4020-2122-4_3.
   Google Scholar
• Niiniluoto, I. 1999. Defending abduction. Philosophy of Science 66 (S3):S436–S451. doi: 10.1086/392744.
   Google Scholar
• Qiu, P. 2018. Jump regression, image processing, and quality control. Quality Engineering 30 (1):137–53. doi: 10.1080/08982112.2017.1357077.
   Web of Science ®Google Scholar
• Reddy, G. P. O. 2018. Digital image processing: Principles and applications. In Geospatial technologies in land resources mapping, monitoring and management. Geotechnologies and the environment, eds. G. P. O. Reddy and S. K. Singh, vol 21, 1–30. Cham: Springer. doi: 10.1007/978-3-319-78711-4_6.
   Google Scholar
• Roberts, S. W. 1959. Control chart tests based on geometric moving averages. Technometrics 1 (3):239–50. doi: 10.1080/00401706.1959.10489860.
   Google Scholar
• Robinson, T. J., R. C. Giles, and R. U. Rajapakshage. 2020. Discussion of “Experiences with big data: Accounts from a data scientist’s perspective. Quality Engineering 32 (4):543–9. doi: 10.1080/08982112.2020.1758333.
   Google Scholar
• Rong, W., Z. Li, W. Zhang, and L. Sun. 2014. An improved Canny edge detection algorithm. IEEE International Conference on Mechatronics and Automation, Tianjin, China, August 3–6, 577–582. doi: 10.1109/ICMA.2014.6885761.
   Google Scholar
• Rosen-Zvi, M., C. Chemudugunta, T. Griffiths, P. Smyth, and M. Steyvers. 2010. Learning author-topic models from text corpora. ACM Transactions on Information Systems 28 (1):1–38. doi: 10.1145/1658377.1658381.
   Web of Science ®Google Scholar
• Rosten, E., and T. Drummond. 2006. Machine learning for high-speed corner detection. Paper presented at the Proceedings of 9th European Conference on Computer Vision, Graz, Austria, May 7–13, vol. 2, 430–43.
   Google Scholar
• Shewhart, W. A. 1931. Economic control of quality of manufactured product. Princeton, NJ: Van Nostrand Reinhold. doi: 10.2307/2277676.
   Google Scholar
• Shewhart, W. A. 1939. Statistical method from the viewpoint of quality control. Washington, DC: Department of Agriculture, The Graduate School USA. (Reprint 1986; New York, NY: Dover Publications.)
   Google Scholar
• Strang, G. 2007. Linear algebra and its applications. 4th ed. Hoboken, NJ: Nelson Engineering.
   Google Scholar
• Teh, Y. W., D. Newman, and M. Welling. 2007. A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation. In Advances in neural information processing systems, eds. B. Schölkopf, J. Platt and T. Hoffman, 1353–60. Vancouver, CA: MIT Press.
   Google Scholar
• Tsai, R. Y. 1987. A versatile camera calibration technique for high accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal on Robotics and Automation 3 (4):323–44. doi: 10.1109/JRA.1987.1087109.
   Google Scholar
• Tukey, J. W. 1977. Exploratory data analysis. Reading, PA: Addison-Wesley.
   Google Scholar
• Vining, G., M. Kulahci, and S. Pedersen. 2016. Recent advances and future directions for quality engineering. Quality and Reliability Engineering International 32 (3):863–75. doi: 10.1002/qre.1797.
   Web of Science ®Google Scholar
• Wu, Z., M. Xie, and S. Zhang. 2005. A virtual system for vision based SPC. Quality Engineering 17 (3):337–43. doi: 10.1081/QEN-200059835.
   Google Scholar
• Zhang, Z. 2000. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 (11):1330–4. doi: 10.1109/34.888718.
   Web of Science ®Google Scholar