Continous Monitoring of Shelf Lives of Materials by Application of Data Loggers With Implemented Kinetic Parameters
1AKTS AG Advanced Kinetics and Technology Solutions, http://www.akts.com, Technopôle 1, 3960 Siders, Switzerland
2armasuisse, Science and Technology Centre, http://www.armasuisse.ch, 3602 Thun, Switzerland
3PB Clermont EURENCO Group, Rue de Clermont 176, 4480 Engis, Belgium
4School of Engineering and Architecture of Fribourg, HES-SO University of Applied Sciences and Arts Western Switzerland, Bd de Pérolles 80, 1700 Fribourg, Switzerland
Abstract
A procedure is presented in which the continuous evaluation of the shelf life (expiry date) of perishable
goods based on Internet of Things (IoT) paradigm helps in the optimal storage/shipment and results in
significant decrease of waste. The evaluation of the shelf life of e.g. food, pharmaceutical materials,
polymers, energetic materials at room- or daily climate fluctuation temperatures requires the kinetic
analysis at the temperature range which is as much as possible similar to those at which the products
will be stored or transported. The collection of the data at these relatively low temperatures is time and
effort consuming. Therefore, only a limited number of experimental points is generally used for the
evaluation of the deterioration rate. Kinetic analysis of such sparse points requires advanced kinetic
analysis based for example on Akaike and Bayesian information criteria.
We compare the results of the evaluation of the shelf life of propellant and vaccine calculated by
advanced kinetics and simplified 0-th and 1-st order kinetic models. The obtained simulations show that
the application of simplified kinetics or commonly used the Mean Kinetic Temperature approach may
result in an imprecise estimation of the shelf life. The implementation of the kinetic parameters obtained
from advanced kinetic analysis into programmable data loggers allows us in contrast to existing
solutions which only monitor the temperature, the continuous, online evaluation and display on the
smartphone of the actual extent of the deterioration of materials. The proposed approach is universal
and can be used for any goods, any methods of shelf life determination and any type of data loggers.
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Prediction of Thermal Stability of Materials by Modified Kinetic and Model Selection Approaches based on Limited Amount of Experimental Points
1Advanced Kinetics and Technology Solutions AKTS AG http://www.akts.com, TECHNO-Pôle, 3960 Siders, Switzerland
2armasuisse, Science and Technology Centre, http://www.armasuisse.ch, 3602 Thun, Switzerland
3University of Applied Sciences of Western Switzerland, http://www.eif.ch, 1705 Fribourg, Switzerland
Abstract
The experimental data collected in the discontinuous mode are often used for the computation of reaction kinetics and, further, for the simulation of the thermal stability of materials. However, the kinetic calculations based on limited amount of sparse points require specific criteria allowing correct choice of the best kinetic model. We present the modified kinetic computations allowing considering one, two or even more reaction stages by applying unlimited amount of combinations of different kinetic models for the best description of the reaction course. The kinetic parameters are calculated using the truncated Šestâk-Berggren (SB) approach and further verified by using the Akaike and Bayesian information criteria (AIC and BIC, respectively). The proposed method of kinetic and model selection for elaboration of sparse points were checked by the simulation of generated points with known, arbitrarily chosen kinetic parameters containing some scatter. The verified procedure was applied for the prediction of the thermal stability of energetic (propellant) and biological (vaccine) materials characterized by approximately 30 experimental data points. If your institution has access, you may view this paper at:
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