Markov Chain Monte Carlo simulation-based optimization for a production scale milk drying process

Adrián Ferrari*, Soledad Gutiérrez, Gürkan Sin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Spray drying is widely used for dehydration of dairy products and among, the most energy-intensive unit operation in this field. An optimization problem for a production scale milk drying system was implemented and solved, considering plant capacity (maximization) and energy consumption (minimization) as the objective. Decision variables were inputs to the spray unit namely the inlet dry bulb air temperature, concentrate moisture, and dry solids flow rate. Product stickiness conditions and moisture content were the main constraints, which were modeled using mass and energy balances. A non-deterministic derivative free based optimization technique, namely Markov Chain Monte Carlo (MCMC) algorithm was chosen to solve the problem. The results showed that throughput maximization is achieved at the expense of a relative energy consumption penalization in the spray and revealed that the structure of the problem seems to be convex. This study shows a promising non-conventional use of MCMC algorithms in optimization studies.
Original languageEnglish
Title of host publicationProceedings of the 33rd European Symposium on Computer Aided Process Engineering
EditorsAntonis Kokossis, Michael C. Georgiadis, Efstratios N. Pistikopoulos
Volume52
PublisherElsevier
Publication date2023
Pages291-296
ISBN (Print)978-0-443-23553-5, 978-0-443-15274-0
DOIs
Publication statusPublished - 2023
Event33rd European Symposium on Computer Aided Process Engineering - Athens, Greece
Duration: 18 Jun 202321 Jun 2023

Conference

Conference33rd European Symposium on Computer Aided Process Engineering
Country/TerritoryGreece
CityAthens
Period18/06/202321/06/2023
SeriesComputer Aided Chemical Engineering
Volume52
ISSN1570-7946

Fingerprint

Dive into the research topics of 'Markov Chain Monte Carlo simulation-based optimization for a production scale milk drying process'. Together they form a unique fingerprint.

Cite this