Multivariate Key Performance Indicator of Baking Process
Energy efficiency is nowadays a subject deeply discussed in several fields, with a large potential in industry. Here proper process and energy management routines turns out to be essential to reduce the energy demand while keeping the control of the product quality. In this respect the bread baking,...
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| Published in | Energy procedia Vol. 82; pp. 554 - 561 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.01.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1876-6102 1876-6102 |
| DOI | 10.1016/j.egypro.2015.11.869 |
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| Abstract | Energy efficiency is nowadays a subject deeply discussed in several fields, with a large potential in industry. Here proper process and energy management routines turns out to be essential to reduce the energy demand while keeping the control of the product quality. In this respect the bread baking, one of the pillar of food related industry, is an energy intensive process irrespective to the adopted oven technology or to the primary energy nature. Baking is the fundamental step of the bread production process and it entails a number of complex chemical and physical phenomena, critical to the final physical properties of bread, i.e. crust colour, crumb texture and taste. A careful balance throughout all the steps of the “manufacturing” cycle is vital to ensure the processes synchronization, in order to produce a consistent and satisfactory loaf of bread. A proper energy management of this process needs to consider such features to ensure a high quality product. As such process monitoring can not be conveniently described using customary specific energy metric (correlating the energy demand to the amount of processed material) or full three-dimensional (3D) physic-based modeling as in computational fluid dynamics (CFD).
In this paper, the energy analysis of the system is carried out with a methodology rooted in the family of non parametric approaches. The aim of the study is to identify key performance indicators (KPIs) able to assess the effectiveness of the energy “use” along the baking process. Specifically, the identification of KPIs is carried out using Principal Component Analysis (PCA) of the available datasets. |
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| AbstractList | Energy efficiency is nowadays a subject deeply discussed in several fields, with a large potential in industry. Here proper process and energy management routines turns out to be essential to reduce the energy demand while keeping the control of the product quality. In this respect the bread baking, one of the pillar of food related industry, is an energy intensive process irrespective to the adopted oven technology or to the primary energy nature. Baking is the fundamental step of the bread production process and it entails a number of complex chemical and physical phenomena, critical to the final physical properties of bread, i.e. crust colour, crumb texture and taste. A careful balance throughout all the steps of the “manufacturing” cycle is vital to ensure the processes synchronization, in order to produce a consistent and satisfactory loaf of bread. A proper energy management of this process needs to consider such features to ensure a high quality product. As such process monitoring can not be conveniently described using customary specific energy metric (correlating the energy demand to the amount of processed material) or full three-dimensional (3D) physic-based modeling as in computational fluid dynamics (CFD).
In this paper, the energy analysis of the system is carried out with a methodology rooted in the family of non parametric approaches. The aim of the study is to identify key performance indicators (KPIs) able to assess the effectiveness of the energy “use” along the baking process. Specifically, the identification of KPIs is carried out using Principal Component Analysis (PCA) of the available datasets. |
| Author | Feudo, Sara Marchegiani, Andrea Bonacina, Fabrizio De Propris, Luciano Corsini, Alessandro |
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| Keywords | Energy efficiency KPI industrial oven bread baking PCA |
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| References_xml | – reference: A Corsinia, L. De Propris, S. Feudo, M. Stefanato; Assessment of a diagnostic procedure for the monitoring and control of industrial processes; 7th International Conference on Applied Energy – ICAE2015. – reference: Yeh1 AB, Lin DK.J., McGrath R.N., Multivariate Control Charts for Monitoring Covariance Matrix: A Review,” Quality Technology and Quantitative Management, 3, 415-436, 2006. – reference: European Climate Foundation (ECF), RoadMap 2050, 2012 . – reference: Dongellini M., Marinosci C., Morini G.L, Energy audit of an industrial site: a case study, Energy Procedia 45, 2014, p. 424-433. – volume: 103 start-page: 92 year: 2011 end-page: 102 ident: bib0035 article-title: Bread baking: technological considerations based on process modelling and simulation publication-title: J Food Eng – reference: I T Jolliffe; Principal component Analysi; New York: Springer-Verlag Inc.; 1986. – volume: 21 start-page: 81 year: 1985 end-page: 222 ident: bib0025 article-title: Designs, thermal performances and other factors concerning cooking equipment and associated facilities publication-title: Appl Energy – volume: 65 start-page: 599 year: 2004 end-page: 608 ident: bib0030 article-title: modelling and simulation of the temperature profiles and airflow patterns during a continuous industrial baking process publication-title: J Food Eng – volume: 55 start-page: 41 year: 2002 end-page: 48 ident: bib0020 article-title: Optimisation of the temperature profile in bread baking publication-title: J Food Eng – reference: K. Esbensen, P. Geladi, Principal Component Analysis, Umei University, 1987. – reference: Khatir Z, Paton J, Thompson H, Kapur N, Toropov V. Optimisation of the energy efficiency of bread-baking ovens using a combined experimental and computational approach. Applaied Energy 2013; p. 918-927. – reference: Swortfiguer M.J, Dough absorption and moisture retention in bread, Baker Digest, 42 (4) (1968), pp. 42-44. – reference: Haridy S., Wu Z., Industrial Engineering and Management, Univariate and Multivariate Control Charts for Monitoring Dynamic-Behavior Processes: a Case Study 2009-2(3): p. 464-498. – reference: Y C Liang, H P Lee, S P Lim, W Z Lin, C G Wu; Proper Orthogonal Decomposition and its application .- Part I: Theory; Journal of Sound and Vibration; 2002; pp 527-544. – reference: Consumi di energia elettrica in Italia, Database Terna; 2013. – volume: 32 start-page: 709 year: 2009 end-page: 729 ident: bib0040 article-title: Multi-objective optimisation to improve the product range of baking systems publication-title: J Food Process Eng – reference: Khatir Z, Thompson HM, Kapur N, Toropov VV, Paton JB. The application of computational fluid dynamics and design optimisation in the British breadbaking industry. 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| Title | Multivariate Key Performance Indicator of Baking Process |
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