Advanced search
Start date
Betweenand

Development platform of analytical sensors, based on artificial intelligence, applied to industrial biotechnological processes: monitoring of alcoholic fermentation

Grant number: 19/09080-3
Support type:Research Grants - Innovative Research in Small Business - PIPE
Duration: February 01, 2021 - October 31, 2021
Field of knowledge:Engineering - Chemical Engineering - Chemical Process Industries
Principal researcher:Moisés Alves
Grantee:Moisés Alves
Company:Bioprocess Improvement Consultoria e Pesquisas em Bioprocessos Ltda
CNAE: Fabricação de malte, cervejas e chopes
Fabricação de álcool
Fabricação de biocombustíveis, exceto álcool
City: Campinas
Pesquisadores principais:
Daniel Ibraim Pires Atala
Assoc. researchers:Elmer Alberto Ccopa Rivera
Associated scholarship(s):21/00667-1 - Development platform of analytical sensors, based on artificial intelligence, applied to industrial biotechnological processes: monitoring of alcoholic fermentation, BP.PIPE

Abstract

Currently, bioprocesses play a key role in the industry. A bottleneck in monitoring and controlling bioprocesses is often caused by the lack of reliable sensors, particularly for biotechnological variables. A solution to this problem can be found through the design of software sensors, algorithms used to infer variables of difficult measure from simple and low-cost measures. The objective of this project is the development and experimental evaluation of robust software sensor that allows real-time inference of cell, substrate and product concentrations from secondary measures such as pH, temperature, turbidity and CO2 flow for alcoholic fermentation processes on basis the process of batch fermentation. For that, it will be perfomed the elaboration of a database of the variables of the batch fermentation process by means of ten bench tests at different temperatures. LabVIEW® software will be used for data collection of secondary variables and chromatographic analysis to collect the main data. The database and artificial intelligence techniques through artificial neural network (RNA) models will be used for the construction of software sensors that describe the kinetics of the process to meet changing in the fermentation conditions. RNAs will be characterized by three main aspects; architecture, training algorithm and activation function. Finally, the validation of the sensor software will be carried out by means of new tests of the fermentation process, comparing the prediction of the virtual sensors with the results obtained from conventional chromatographic techniques. It is intended, therefore, to obtain an efficient monitoring of the alcoholic fermentation process in real time that allows to make adjustments in the conditions of operation, control and to keep the process operating in the ideal conditions. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
Articles published in other media outlets (0 total):
More itemsLess items
VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)