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    Publisher: Academic Journals Inc., USA
   
  International Journal of Manufacturing System serves as an international platform for professionals, researchers and educators to publish the current research in the field of manufacturing and system. Scope of the journal includes: products, equipment, information, control and support functions for the economical and competitive development, production, delivery and total life cycle of products to satisfy market and social needs.

Submit your best paper to this journal via online submission system.
  Editor-in-Chief:  Atul Borade Borade
 
 
Carfagni, M. and R. Furferi, 2007. The colorimetric measurement of melange woollen yarns: A new optical tool. J. Eng. Applied Sci., 2: 877-881.
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Carfagni, M., R. Furferi and L. Governi, 2005. A real-time machine-vision system for monitoring the textile raising process. Comput. Ind., 56: 831-842.
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Furferi, R. and L. Governi, 2006. Development of an artificial vision inspection system for real-time defect detection and classification on circular knitting machines. Wseas Trans. Comput., 5: 1186-1194.
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Furferi, R. and L. Governi, 2008. Machine vision tool for real-time detection of defects on textile raw fabrics. J. Text. Inst., 99: 57-66.
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Furferi, R. and L. Governi, 2008. The recycling of wool clothes: An artificial neural network colour classification tool. Int. J. Adv. Manufacturing Technol., 37: 722-731.
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Furferi, R. and L. Governi, 2010. Prediction of the spectrophotometric response of a carded fibre composed by different kind of differently coloured raw materials: An artificial neural network based approach. Color Res. Appl., DOI: 10.1002/col.20623.
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Furferi, R. and M. Carfagni, 2010. An as-short-as-possible mathematical assessment of spectrophotometric color matching. J. Applied Sci., 10: 2108-2114.
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Furferi, R. and M. Carfagni, 2010. Prediction of the colour and of the colour solidity of a jigger dyed cellulose based fabric: A cascade neural network approach. Textile Res. J., DOI: 10.1177/0040517510365952.
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Furferi, R., L. Governi and Y. Volpe, 2010. ANN-based method for olive ripening index automatic prediction J. Food Eng., DOI: 10.1016/j.jfoodeng.2010.07.016.
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Furferi, R., M. Carfagni and F. Miniati, 2005. Design and optimization of a new range of low sound emission generating set. Electronic J. Tech. Acoustic, .
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Furferi, R., M. Carfagni and M. Daou, 2007. Artificial neural network software for real-time estimation of olive oil qualitative parameters during continuous extraction. Comput. Electronics Agric., 56: 830-842.
Furferi, R., M. Carfagni and M. Daou, 2008. Real-time estimation of peroxides and acidity level of extra-virgin olive oil: An integrated approach. Int. J. Math. Comput. Simulat., 2: 206-214.
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