scholarly journals Sustainable Method Using Filtering Techniques for a Fermentation Process State Estimation

2020 ◽  
Vol 12 (17) ◽  
pp. 7105 ◽  
Author(s):  
Anca Sipos
Keyword(s):  
Kalman Filter ◽  
Fermentation Process ◽  
Alcoholic Fermentation ◽  
Batch Process ◽  
Performance Criterion ◽  
Monitoring And Control ◽  
Error Norm ◽  
Process Monitoring And Control ◽  
The Difference ◽  
Filtering Techniques

Winemaking is concerned about sustainable energy availability that implies new methods for process monitoring and control. The aim of this paper is to realize a comparative analysis of the possibilities offered using estimation techniques, balances, and filtering techniques such as the Kalman filter (KF) and the extended Kalman filter (EKF), to obtain indirect information about the alcoholic fermentation process during winemaking. Thus, an estimation solution of the process variables in the exponential growing phase is proposed, using an extended observer. In addition, two estimation solutions of this process with the EKF and an estimation of the decay phase of the fermentation process are presented. The difference between the two EKF variants consisted of taking into consideration the indicator of the integral of the error norm square for the second EKF, for which the performance criterion was the statistical average of this indicator. Results from the simulation of the estimation programs of the two EKF variants were more than satisfactory. This research provides a basis for using an EKF designed for advanced control of the alcoholic fermentation batch process as a knowledge-based system.

scholarly journals A Knowledge-Based System as a Sustainable Software Application for the Supervision and Intelligent Control of an Alcoholic Fermentation Process

2020 ◽  
Vol 12 (23) ◽  
pp. 10205
Author(s):  
Anca Sipos
Keyword(s):  
Intelligent Control ◽  
Fermentation Process ◽  
Production Efficiency ◽  
Alcoholic Fermentation ◽  
Control Level ◽  
Exponential Growth Phase ◽  
Monitoring And Control ◽  
Software Application ◽  
Knowledge Based System ◽  
Knowledge Based

One goal of specialists in food processing is to increase production efficiency in accordance with sustainability by optimising the consumption of raw food materials, water, and energy. One way to achieve this purpose is to develop new methods for process monitoring and control. In the winemaking industry, there is a lack of procedures regarding the common work based on knowledge acquisition and intelligent control. In the present article, we developed and tested a knowledge-based system for the alcoholic fermentation process of white winemaking while considering the main phases: the latent phase, exponential growth phase, and decay phase. The automatic control of the white wine’s alcoholic fermentation process was designed as a system on three levels. Level zero represents the measurement and adjustment loops of the bioreactor. At the first level of control, the three phases of the process are detected functions of the characteristics of the fermentation medium (the initial substrate concentration, the nitrogen assimilable content, and the initial concentration of biomass) and, thus, functions on the phase’s duration. The second level achieves the sequence supervision of the process (the operation sequence of a fermentation batch) and transforms the process into a continuous one. This control level ensures the quality of the process as well as its diagnosis. This software application can be extended to the industrial scale and can be improved by using further artificial intelligence techniques.

Achieving Procedure of a Kinetic Model to Predict the Influence of the Process Global Temperature on a Technological Alcoholic Fermentation II. An Arrhenius type Kinetic Model

2008 ◽  
Vol 59 (4) ◽  
Author(s):  
Neculai Catalin Lungu ◽  
Maria Alexandroaei
Keyword(s):  
Experimental Data ◽  
Saccharomyces Cerevisiae ◽  
Kinetic Model ◽  
Economic Efficiency ◽  
Fermentation Process ◽  
Alcoholic Fermentation ◽  
Global Temperature ◽  
Medium Temperature ◽  
Biotechnological Process

The aim of the present work is to offer a practical methodology to realise an Arrhenius type kinetic model for a biotechnological process of alcoholic fermentation based on the Saccharomyces cerevisiae yeast. Using the experimental data we can correlate the medium temperature of fermentation with the time needed for a fermentation process under imposed conditions of economic efficiency.

scholarly journals Impact of media components from different suppliers on enterokinase productivity in Pichia pastoris

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ján Krahulec ◽  
Martin Šafránek
Keyword(s):  
Recombinant Proteins ◽  
Fermentation Process ◽  
High Impact ◽  
Production Level ◽  
Media Component ◽  
Component Supplier ◽  
The Media ◽  
The Difference ◽  
Optimisation Procedure ◽  
The Ideal

Abstract Background The aim of this study was to provide an information about the homogeneity on the level of enterokinase productivity in P. pastoris depending on different suppliers of the media components. Results In previous studies, we performed the optimisation process for the production of enterokinase by improving the fermentation process. Enterokinase is the ideal enzyme for removing fusion partners from target recombinant proteins. In this study, we focused our optimization efforts on the sources of cultivation media components. YPD media components were chosen as variables for these experiments. Several suppliers for particular components were combined and the optimisation procedure was performed in 24-well plates. Peptone had the highest impact on enterokinase production, where the difference between the best and worst results was threefold. The least effect on the production level was recorded for yeast extract with a 1.5 fold difference. The worst combination of media components had a activity of only 0.15 U/ml and the best combination had the activity of 0.88 U/ml, i.e., a 5.87 fold difference. A substantially higher impact on the production level of enterokinase was observed during fermentation in two selected media combinations, where the difference was almost 21-fold. Conclusions Results demonstrated in the present study show that the media components from different suppliers have high impact on enterokinase productivity and also provide the hypothesis that the optimization process should be multidimensional and for achieving best results it is important to perform massive process also in terms of the particular media component supplier .

scholarly journals From Black Box to Machine Learning: A Journey through Membrane Process Modelling

Membranes ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 574
Author(s):  
Claudia F. Galinha ◽  
João G. Crespo
Keyword(s):  
Machine Learning ◽  
Process Modelling ◽  
Model Membrane ◽  
Point Of View ◽  
Personal Perspective ◽  
Process Conditions ◽  
Monitoring And Control ◽  
Membrane Processes ◽  
Mechanistic Modelling ◽  
Process Monitoring And Control

Membrane processes are complex systems, often comprising several physicochemical phenomena, as well as biological reactions, depending on the systems studied. Therefore, process modelling is a requirement to simulate (and predict) process and membrane performance, to infer about optimal process conditions, to assess fouling development, and ultimately, for process monitoring and control. Despite the actual dissemination of terms such as Machine Learning, the use of such computational tools to model membrane processes was regarded by many in the past as not useful from a scientific point-of-view, not contributing to the understanding of the phenomena involved. Despite the controversy, in the last 25 years, data driven, non-mechanistic modelling is being applied to describe different membrane processes and in the development of new modelling and monitoring approaches. Thus, this work aims at providing a personal perspective of the use of non-mechanistic modelling in membrane processes, reviewing the evolution supported in our own experience, gained as research group working in the field of membrane processes. Additionally, some guidelines are provided for the application of advanced mathematical tools to model membrane processes.

Study Progress on Grinding Surface Residual Stresses for Nano-Ceramic Coatings

2013 ◽  
Vol 753-755 ◽  
pp. 277-280 ◽  
Author(s):  
Wei Xiang Liu
Keyword(s):  
Residual Stress ◽  
High Hardness ◽  
Ceramic Materials ◽  
Ceramic Coatings ◽  
Grinding Process ◽  
Monitoring And Control ◽  
Surface Residual Stress ◽  
Surface Residual Stresses ◽  
Process Monitoring And Control ◽  
Grinding Mechanism

Nano-ceramic materials had high hardness and wear resistance. Combined with current technology and cost saving, nanostructured coatings technology were carried out, using HVOF ( high velocity oxygen fuel) or plasma spraying technique can obtain high quality ceramic coating on metal substrate. Ceramic coatings produced cracks in the grinding due to grinding surface residual stress. the coatings grinding surface residual stress of engineering ceramics have been researched, grinding surface residual stress in the nanostructured ceramic coatings are being researched. the researches in this field include grinding process modeling, abrasives and grinding parameters, grinding process monitoring and control and realization of the software, the grinding mechanism and grinding damage on the surface, grinding force prediction, on-line detection, grinding on nanocoating material is a multivariable complex process.

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