This work is an application of S-Curve analysis to a data series extracted from papers and patents from 2 drying and sterilisation unit operations. A set of data was collected along a timeline. Nonlinear regression techniques were used to calculate the inflection point in the series of patents and papers of both operations. The statistics used to validate the results were adjusted by R2, T-value and Durbin Watson. The data analyses were based on such models as Weibull, Gompertz, logistic, sigmoidal, Hill, among others. Thirteen models were applied. The models used were the best statiscally adjusted ones, from which the inflection point was then calculated. For the patent data, the selected models were sigmoidal for drying and Gompertz for sterilisation. The respective inflection points were located in the years 2002 and 2000. For papers data, the selected models were Hill for drying and sigmoidal for sterilisation. The respective inflection points were located in the years 2019 and 2014. These inflection points calculated over the corresponding S-Curve allow for reduction of the uncertainty in making investment decisions regarding the use of technologies similar to drying and food sterilization. This reduction of the uncertainty can be useful to define the state of technologies (before and after their inflection points), to determine the correct moment to apply mechanisms of intellectual property and technology law, and to establish appropriate strategies.
|Translated title of the contribution||Technology life cycle analysis by S-Curve: Application to food unit operations|
|Number of pages||1|
|State||Published - 2014|