Berthold J, Imkamp D. Looking at the future of manufacturing metrology: Roadmap document of the German VDI/VDE Society for Measurement and Automatic Control. J Sensors Sens Syst. 2013; 2(1):1–7.
Stojadinovic SM, Majstorovic VD, Durakbasa NM, Gaska A, Sładek J. Development of a coordinate measuring machine—based inspection planning system for industry 4.0. Appl Sci. 2021; 11(18).
Lazzari A, Pou JM, Dubois C, Leblond L. Smart metrology: The importance of metrology of decisions in the big data era. IEEE Instrum Meas Mag. 2017; 20(6):22–9.
Stojadinovic SM, Majstorovic VD, Durakbasa NM, Sibalija TV. Towards an intelligent approach for CMM inspection planning of prismatic parts. Meas J Int Meas Confed [Internet]. 2016; 92:326–39. Available from: https://doi.org/http%3A//dx.doi.org/10.1016/j.measurement.2016.06.037
Kasprzak B, Pękala J, Stępień AF, Świerczyński Z. Metrology and measurement systems. Architecture. 2010; XVII(4):537–47.
Zhao Y, Xu X, Kramer T, Proctor F, Horst J. Dimensional metrology interoperability and standardization in manufacturing systems. Comput Stand Interfaces [Internet]. 2011; 33(6):541–55. Available from: https://doi.org/http%3A//dx.doi.org/10.1016/j.csi.2011.02.009
Saif Y, Yusof Y, Latif K, Kadir AZA, lliyas Ahmed M. Systematic review of STEP-NC-based inspection. Vol. 108, International Journal of Advanced Manufacturing Technology. Springer; 2020. p. 3619–44.
Iliyas Ahmad M, Yusof Y, Daud ME, Latiff K, Abdul Kadir AZ, Saif Y. Machine monitoring system: a decade in review. Int J Adv Manuf Technol [Internet]. 2020; 108(11–12):3645–59. Available from: https://doi.org/10.1007/s00170-020-05620-3
Saif Y, Yusof Y, Latif K, Abdul Kadir AZ, Ahmad M binti I, Adam A, et al. Development of a smart system based on STEP-NC for machine vision inspection with IoT environmental. Int J Adv Manuf Technol. 2021;1–18.
Batchelor BG. Machine vision handbook. Machine Vision Handbook. 2012. 1355–1560 p. 11. Sanz JLC, PetkoviC´ D. Machine Vision Algorithms for Automated Inspection of Thin-Film Disk Heads.
IEEE Trans Pattern Anal Mach Intell [Internet]. 1988; 10(6):830–48. Available from: https://ieeexplore.ieee.org/document/9106
You BJ, Oh YS, Bien Z. A Vision System for an Automatic Assembly Machine of Electronic Components. IEEE Trans Ind Electron [Internet]. 1990; 37(5):349–57. Available from: https://ieeexplore.ieee.org/document/103429
Elmasry G, Cubero S, Molto´ E, Blasco J. In-line sorting of irregular potatoes by using automated computer-based machine vision system. J Food Eng [Internet]. 2012; 112(1–2):60–8. Available from: https://doi.org/http%3A//dx.doi.org/10.1016/j.jfoodeng.2012.03.027
Sofu MM, Er O, Kayacan MC, Cetişli B. Design of an automatic apple sorting system using machine vision. Comput Electron Agric. 2016; 127:395–405.
Davies ER. Computer vision for automatic sorting in the food industry. In: Computer Vision Technology in the Food and Beverage Industries [Internet]. University of London, UK: Woodhead Publishing Limited; 2012. p. 150–80. http://dx.doi.org/10.1533/9780857095770.2.150
Nerakae P, Uangpairoj P, Chamniprasart K. Using Machine Vision for Flexible Automatic Assembly System. Procedia Comput Sci [Internet]. 2016; 96(September):428–35. Available from: https://doi.org/http%3A//dx.doi.org/10.1016/j.procs.2016.08.090
Wu Wen-Yen, Mao-Jim J. Wang C-ML. Automated inspection of printed circuit boards. Intell Syst Technol Appl Six Vol Set [Internet]. 1996; 28:103–11. Available from: https://www.sciencedirect.com/science/article/abs/pii/0166361595000631
Golnabi H, Asadpour A. Design and application of industrial machine vision systems. Robot Comput Integr Manuf [Internet]. 2007; 23(6):630–7. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0736584507000233
Wang T, Chen Y, Qiao M, Snoussi H. A fast and robust convolutional neural network-based defect detection model in product quality control. Int J Adv Manuf Technol. 2018; 94(9–12):3465–71.
Liao Z, Abdelhafeez A, Li H, Yang Y, Diaz OG, Axinte D. State-of-the-art of surface integrity in machining of metal matrix composites. Int J Mach Tools Manuf. 2019; 143:63–91.
Kim DH, Kim TJ, Wang X, Kim M, Quan YJ, Oh JW, et al. Smart Machining Process Using Machine Learning: A Review and Perspective on Machining Industry. Int J Precis Eng Manuf—Green Technol. 2018; 5(4):555–68.
Bulnes FG, Usamentiaga R, Garcia DF, Molleda J. An efficient method for defect detection during the manufacturing of web materials. J Intell Manuf [Internet]. 2016; 27(2):431–45. Available from: https://doi.org/http%3A//dx.doi.org/10.1007/s10845-014-0876-9
Song K, Yan Y. A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects. Appl Surf Sci [Internet]. 2013; 285:858–64. Available from: https://doi.org/http% 3A//dx.doi.org/10.1016/j.apsusc.2013.09.002
Zhang Huang, Shen Xingquan, Bo Arixin, Li Yaoming, Zhan Haifei, & Gu Y. Amultiscale evaluation of the surface integrity in boring trepanning association deep hole drilling. Int J Mach Tools Manuf. 2017;123:48–56.
Rao X, Zhang F, Lu Y, Luo X, Chen F. Surface and subsurface damage of reaction-bonded silicon carbide induced by electrical discharge diamond grinding. Int J Mach Tools Manuf. 2020; 154.
Huang SH, Pan YC. Automated visual inspection in the semiconductor industry: A survey. Comput Ind [Internet]. 2015; 66:1–10. Available from: https://doi.org/http%3A//dx.doi.org/10.1016/j.compind.2014.10.006
Ravimal D, Kim H, Koh D, Hong JH, Lee SK. Image-Based Inspection Technique of a Machined Metal Surface for an Unmanned Lapping Process. Int J Precis Eng Manuf—Green Technol [Internet]. 2020; 7 (3):547–57. Available from: https://doi.org/10.1007/s40684-019-00181-7
Ren Z, Fang F, Yan N, Wu Y. State of the Art in Defect Detection Based on Machine Vision. Int J Precis Eng Manuf—Green Technol [Internet]. 2021; https://doi.org/10.1007/s40684-021-00343-6
Penumuru DP, Muthuswamy S, Karumbu P. Identification and classification of materials using machine vision and machine learning in the context of industry 4.0. J Intell Manuf [Internet]. 2020; 31(5):1229–41. Available from: https://doi.org/10.1007/s10845-019-01508-6
Ali MAH, Lun AK. A cascading fuzzy logic with image processing algorithm–based defect detection for automatic visual inspection of industrial cylindrical object’s surface. Int J Adv Manuf Technol. 2019; 102 (1–4):81–94.