Artificial intelligence based system to improve the inspection of plastic mould surfaces

Plastic industry is today in a constant growth, demanding several products from other segments, which includes the plastic moulds, used mainly in the injection moulding process. This paper presents a methodology for the surface evaluation of plastic moulds, aiming the automation of the polishing surface analysis. Provided that this type of analysis by traditional procedures can be slow and expensive, the development of automatic system could lead to considerable improvements regarding the speed and reliability of information. The starting point of the evaluation procedure is the image generated by the laser light scattered over the sample mould surface that could be captured and analysed by image processing and artificial intelligence techniques. The results showed that the proposed system is able to mapping and classifying several damages over the polished surface and could be an alternative to reduce efficiently the costs and the spending time in mould surface inspection tasks.

[1]  W. L. Chan,et al.  An integrated FEM and ANN methodology for metal-formed product design , 2008, Eng. Appl. Artif. Intell..

[2]  J. Ramkumar,et al.  Rotational abrasive flow finishing (R-AFF) process and its effects on finished surface topography , 2010 .

[3]  Te-Hsiu Sun,et al.  Automated thermal fuse inspection using machine vision and artificial neural networks , 2016, J. Intell. Manuf..

[4]  Der-Baau Perng,et al.  Automatic optical inspection system for IC molding surface , 2016, J. Intell. Manuf..

[5]  Stanislaw Osowski,et al.  Automatic recognition of industrial tools using artificial intelligence approach , 2013, Expert Syst. Appl..

[6]  Sami Ekici,et al.  Support vector machines models for surface roughness prediction in CNC turning of AISI 304 austenitic stainless steel , 2012, J. Intell. Manuf..

[7]  R. Srinivasan,et al.  MREF-ECM process for hard passive materials surface finishing , 2001 .

[8]  Paul Wintz,et al.  Digital image processing (2nd ed.) , 1987 .

[9]  Vladimir Pucovsky,et al.  Application of fuzzy logic and regression analysis for modeling surface roughness in face milliing , 2013, J. Intell. Manuf..

[10]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[11]  Han-Ming Chow,et al.  Finishing effects of spiral polishing method on micro lapping surface , 2007 .

[12]  I. Jolliffe.  Principal Component Analysis , 2002 .

[13]  Andrés Bustillo,et al.  Using artificial intelligence to predict surface roughness in deep drilling of steel components , 2011, Journal of Intelligent Manufacturing.

[14]  Hae Yong Kim,et al.  Ciratefi: An RST-invariant template matching with extension to color images , 2011, Integr. Comput. Aided Eng..

[15]  Guilian Wang,et al.  Process optimization of the serial-parallel hybrid polishing machine tool based on artificial neural network and genetic algorithm , 2010, Journal of Intelligent Manufacturing.

[16]  Marian Stewart Bartlett,et al.  A comparison of Gabor filter methods for automatic detection of facial landmarks , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[17]  Z. H. Che,et al.  PSO-based back-propagation artificial neural network for product and mold cost estimation of plastic injection molding , 2010, Comput. Ind. Eng..

[18]  Rajiv Shivpuri,et al.  On line prediction of surface defects in hot bar rolling based on Bayesian hierarchical modeling , 2015, J. Intell. Manuf..

[19]  Potsang B. Huang.  An intelligent neural-fuzzy model for an in-process surface roughness monitoring system in end milling operations , 2014, Journal of Intelligent Manufacturing.

[20]  Rafael Agnelli Mesquita,et al.  Tool steel quality and surface finishing of plastic molds , 2010 .

[21]  D. Sagi,et al.  Gabor filters as texture discriminator , 1989, Biological Cybernetics.

[22]  Zhen Qian,et al.  Highly sensitive size discrimination of sub-micron objects using optical Fourier processing based on two-dimensional Gabor filters. , 2009, Optics express.

[23]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.