Documents disponibles écrits par cet auteur

Analysis and classification of the paper surface / Marco S. Reis in Industrial & engineering chemistry research, Vol. 49 N° 5 (Mars 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 5 (Mars 2010) . - pp. 2493–2502 Titre : Analysis and classification of the paper surface Type de document : texte imprimé Auteurs : Marco S. Reis, Auteur ; Pedro M. Saraiva, Auteur Année de publication : 2010 Article en page(s) : pp. 2493–2502 Note générale : Idustrial Chemistry Langues : Anglais (eng) Mots-clés : Paper  Surface Résumé : Growing demands on paper quality impel papermakers to found new, robust, and reliable methodologies to evaluate paper properties, directly aligned with consumer preferences. In this paper, we address the development of such methodologies, focused on two different aspects of the paper surface: surface roughness and surface waviness. Using profilometry measurements and quality assessments made by a panel of experts, we have developed and tested several classification methodologies in order to emulate their evaluations, by combining different feature extraction techniques with classifiers representing a variety of statistical methods commonly applied. The current standard method to infer roughness, the Bendtsen tester, was also analyzed, in order to cast some light on how its measurements are affected by fundamental parameters of the paper surface. Results obtained show that it is indeed possible to develop a suitable classifier for inferring the quality of paper roughness in three classes (good/medium/bad) and for paper waviness in two classes (good/not good). Note de contenu : Bibliogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901688w [article] Analysis and classification of the paper surface [texte imprimé] / Marco S. Reis, Auteur ; Pedro M. Saraiva, Auteur . - 2010 . - pp. 2493–2502. Idustrial Chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 5 (Mars 2010) . - pp. 2493–2502 Mots-clés : Paper  Surface Résumé : Growing demands on paper quality impel papermakers to found new, robust, and reliable methodologies to evaluate paper properties, directly aligned with consumer preferences. In this paper, we address the development of such methodologies, focused on two different aspects of the paper surface: surface roughness and surface waviness. Using profilometry measurements and quality assessments made by a panel of experts, we have developed and tested several classification methodologies in order to emulate their evaluations, by combining different feature extraction techniques with classifiers representing a variety of statistical methods commonly applied. The current standard method to infer roughness, the Bendtsen tester, was also analyzed, in order to cast some light on how its measurements are affected by fundamental parameters of the paper surface. Results obtained show that it is indeed possible to develop a suitable classifier for inferring the quality of paper roughness in three classes (good/medium/bad) and for paper waviness in two classes (good/not good). Note de contenu : Bibliogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901688w

Prediction of profiles in the process industries / Marco S. Reis in Industrial & engineering chemistry research, Vol. 51 N° 11 (Mars 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 11 (Mars 2012) . - pp. 4254–4266 Titre : Prediction of profiles in the process industries Type de document : texte imprimé Auteurs : Marco S. Reis, Auteur ; Pedro M. Saraiva, Auteur Année de publication : 2012 Article en page(s) : pp. 4254–4266 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Prediction  Process  industries Résumé : The characterization of products and processes by space- or time-related sets of measurements (profiles) is becoming an increasingly common situation in today’s highly instrumentalized manufacturing systems. Even though many applications and methodologies in which profile measurements are employed as inputs to analysis tasks have already been proposed and described, problems in which they naturally appear as outputs are rare. Therefore, in this work, we present real-world applications in which profiles are the desired prediction targets and describe the methodologies followed to address the underlying analysis goals. In this context, we show how to properly establish the sample-specific prediction intervals for profiles, in a simple and flexible way, through nonparametric resampling or noise addition procedures. The added value of the various analyses carried out during the description of the case studies is also highlighted from the standpoint of the associated benefits for process improvement. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie300390h [article] Prediction of profiles in the process industries [texte imprimé] / Marco S. Reis, Auteur ; Pedro M. Saraiva, Auteur . - 2012 . - pp. 4254–4266. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 11 (Mars 2012) . - pp. 4254–4266 Mots-clés : Prediction  Process  industries Résumé : The characterization of products and processes by space- or time-related sets of measurements (profiles) is becoming an increasingly common situation in today’s highly instrumentalized manufacturing systems. Even though many applications and methodologies in which profile measurements are employed as inputs to analysis tasks have already been proposed and described, problems in which they naturally appear as outputs are rare. Therefore, in this work, we present real-world applications in which profiles are the desired prediction targets and describe the methodologies followed to address the underlying analysis goals. In this context, we show how to properly establish the sample-specific prediction intervals for profiles, in a simple and flexible way, through nonparametric resampling or noise addition procedures. The added value of the various analyses carried out during the description of the case studies is also highlighted from the standpoint of the associated benefits for process improvement. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie300390h

Quality control of food products using image analysis and multivariate statistical tools / Ana C Pereira in Industrial & engineering chemistry research, Vol. 48 N°2 (Janvier 2009)

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 48 N°2 (Janvier 2009) . - p 988–998 Titre : Quality control of food products using image analysis and multivariate statistical tools Type de document : texte imprimé Auteurs : Ana C Pereira, Auteur ; Marco S. Reis, Auteur ; Pedro M. Saraiva, Auteur Année de publication : 2009 Article en page(s) : p 988–998 Note générale : chemical engineering Langues : Anglais (eng) Mots-clés : food  products--Quality  Control Résumé : Visual appearance is an important feature in the quality assessment of food products, since it plays a key role in the decisions made by consumers. Frequently, its evaluation is carried out by a panel of experts from the quality department who analyze, by visual inspection, samples of product taken from the process. It is well-known that such methodologies of assessment suffer from several drawbacks, such as subjectivity, limited precision, and lack of stability over time, even for well-trained personnel, although extensive training programs can improve assessment performance. In this context, we present in this paper results regarding the development of an automated methodology for assessing the visual appearance of cereal flakes, in what concerns a particular quality feature, relative to the existence of regions where cereal coating is inadequate. The proposed procedure is able to extract the necessary information from images taken from product samples, leading to an objective, stable, and quantitative quality control measurement system for this property. The developed algorithm essentially consists of implementing a supervised classification methodology, based on the estimated Mahalanobis distance for assessing proximity in the color space, while incorporating the natural variability and color correlations found in cereal flakes. This procedure also integrates fuzzy logic reasoning for samples falling under regions closer to the classes’ boundaries. Results obtained from a real industrial plant indicate that it is indeed possible to classify different samples of flakes according to classes previously defined. They also provide a sound basis for further developments, in particular regarding the generation of metrics for quality assessment and the implementation of a similar procedure online and in situ. [article] Quality control of food products using image analysis and multivariate statistical tools [texte imprimé] / Ana C Pereira, Auteur ; Marco S. Reis, Auteur ; Pedro M. Saraiva, Auteur . - 2009 . - p 988–998. chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 48 N°2 (Janvier 2009) . - p 988–998 Mots-clés : food  products--Quality  Control Résumé : Visual appearance is an important feature in the quality assessment of food products, since it plays a key role in the decisions made by consumers. Frequently, its evaluation is carried out by a panel of experts from the quality department who analyze, by visual inspection, samples of product taken from the process. It is well-known that such methodologies of assessment suffer from several drawbacks, such as subjectivity, limited precision, and lack of stability over time, even for well-trained personnel, although extensive training programs can improve assessment performance. In this context, we present in this paper results regarding the development of an automated methodology for assessing the visual appearance of cereal flakes, in what concerns a particular quality feature, relative to the existence of regions where cereal coating is inadequate. The proposed procedure is able to extract the necessary information from images taken from product samples, leading to an objective, stable, and quantitative quality control measurement system for this property. The developed algorithm essentially consists of implementing a supervised classification methodology, based on the estimated Mahalanobis distance for assessing proximity in the color space, while incorporating the natural variability and color correlations found in cereal flakes. This procedure also integrates fuzzy logic reasoning for samples falling under regions closer to the classes’ boundaries. Results obtained from a real industrial plant indicate that it is indeed possible to classify different samples of flakes according to classes previously defined. They also provide a sound basis for further developments, in particular regarding the generation of metrics for quality assessment and the implementation of a similar procedure online and in situ.