Abstract
In order to become more competitive, manufacturing companies exploit new technologies and practices that can improve their production efficiency, and reduce the number of rejected products. This work is about a Monitoring and Data Analysis System (MDAS), a software system that combines data mining, neural networks modelling and graphical data analysis to assist the company in identifying patterns, trends or problems that increase the risk of rejected products. A pilot version of the proposed system is tested on two production lines of a pharmaceutical company and has identified previously unknown patterns and trends that were hindering the quality of the end product. Since the operation of the proposed system does not affect the production it is suitable for industries bound by strict regulation. In general, the proposed system could be adopted for other products and industries.
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Alexopoulos, T., Packianather, M. (2017). A Monitoring and Data Analysis System to Achieve Zero-Defects Manufacturing in Highly Regulated Industries. In: Campana, G., Howlett, R., Setchi, R., Cimatti, B. (eds) Sustainable Design and Manufacturing 2017. SDM 2017. Smart Innovation, Systems and Technologies, vol 68. Springer, Cham. https://doi.org/10.1007/978-3-319-57078-5_30
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DOI: https://doi.org/10.1007/978-3-319-57078-5_30
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