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Facoltà di Scienze Agrarie e Alimentari Università degli Studi di Milano
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Process modeling, optimization and innovation
Code: G6009-
Teacher:  Alyssa Mariel Hidalgo Vidal
CFU subdivision: Lectures: 4
Practices in classroom: 2
Basic aims:  Aim of the course is to make the student familiar with the theory and practice of the modeling and optimization methods most used in the food industry and to present a selection of new technologies, alternative to traditional, also describing their innovative features and potential applications.
Acquired skills:  Through the use of the design expert software, the student will be able to build statistical models which describe a production process. The models will be used to optimize the operative conditions and predict the properties of the finished product. The student will also acquire the basic knowledge on some innovative technologies in order to evaluate the potential applications in the different food production processes.
Course contents:  1. Aims and properties of the process modeling 2. The different statistical methods used to build a model 3. The full factorial and fractionated designs 4. The surface responce methods 5. The optimization and the desirability function 6. The mixture design 7. Novel food processing 8. Computer aided practice
Program:  1. Introduction to process modeling. Comparison between the fundamental and the empirical approach. Principles, definitions, aims, examples of application. 2. The different statistical methods used for model building: linear, non linear and weighted regressions. The least square method to estimate model parameters. 3. Principles, aims and procedures of experimental design. The choosing criteria among the different experimental designs. The analysis of variance. The one factor comparative design and the use of blocking. The two-level full and fractional factorial designs. The principles of confounding and design resolution. Methods to improve the resolution of fractional design. The Plackett-Burman designs. The addition of centre points to factorial design. 4. The response surface designs: Central Composite and Box-Behnken designs. 5. The optimization procedures for single or multiple response. The desirability function. 6. The mixture designs: simplex lattice and simplex centroids. Combining mixture and process factors: D-optimal design. 7. Thermal and non thermal novel food processing. High pressure, pulsed electric field, microwave, and ohmic heating processes. 8. Computer practice for the modeling and optimization of food process and products by applying the different design methods. Softwares: Excel and Design Expert.
Prerequisites:  The knowledge of the basic unit operations for the food industry is required, besides some basic statistical principles.
Preparatory instructions:  None
Learning materials:  The files with the teaching slides and note pages are made available. The text of the computer exercises with explicative notes are given.
Recommended books:
- “Progettazione e analisi degli esperimenti”, Douglas Montgomery, McGraw-Hill.
- “Engineering statistics”
- Response Surface Methodology. Process and product optimization using design experiments. Wiley series in probability and statistics. Raymond H. Myers, Douglas C. Montgomery, Christine M. Anderson-Cook
Other info:  The examination is comprised of two separate tests. In the first practical test, the student is asked to solve problems of process modeling/optimization using a dedicated software on a computer. Moreover he should reply in writing to a set of questions concerning the solved problem and give comments on the results obtained.
In the second test (written test), the student is asked to reply to a set of questions aimed at evaluating the theoretical skills acquired on the methods for process modeling and optimization and on the innovative technologies and their possible uses for food productions.
At least a 18 mark is required in the first practical test to have access to the second written test. The final mark is the arithmetic mean of the marks of the two tests.
Program of Process modeling, optimization and innovation (pdf version)
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