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

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Abstract

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.

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Acknowledgments

The authors would like to thank Uninove, CAPES and CNPq for the scholarship granted to two of the authors, as well as Villares Metals for providing the samples of polished moulds.

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Authors and Affiliations

  1. Industrial Engineering Post-Graduation Program, Nove de Julho University - UNINOVE, Av. Francisco Matarazzo, 612, Água Branca, São Paulo, SP, 05001-100, Brazil

    André. F. H. Librantz, Sidnei A. de Araújo, Wonder A. L. Alves, Peterson A. Belan, Rafael A. Mesquita & Antonio H. P. Selvatici

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  1. André. F. H. Librantz
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  2. Sidnei A. de Araújo
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  3. Wonder A. L. Alves
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  4. Peterson A. Belan
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  5. Rafael A. Mesquita
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  6. Antonio H. P. Selvatici
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Correspondence to André. F. H. Librantz.

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Librantz, A.F.H., de Araújo, S.A., Alves, W.A.L. et al. Artificial intelligence based system to improve the inspection of plastic mould surfaces. J Intell Manuf 28, 181–190 (2017). https://doi.org/10.1007/s10845-014-0969-5

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  • DOI: https://doi.org/10.1007/s10845-014-0969-5

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