Developing Thermal Data Analysis Standards: Algorithms for Developing Temperature Test Profiles from Ambient Lane Data
Currently standards such as ISTA 7D or 7E specify standard temperature test profiles. However, there is great advantage in standardizing the cold chain algorithms used to analyze input data (such as ambient lane temperature profiles) and from this analysis make (good) decisions about the suitability of a container for a particular shipping application.
This paper describes in detail the QT(min/max) algorithm for developing thermal profiles and demonstrates how it is superior to some existing algorithms that are currently in use. It is proposed that this QT(min/max) algorithm should become a standard algorithm for analyzing ambient lane data in order to define OQ test temperature profiles. This algorithm is a critical element in an overall risk evaluation for evaluating pre-qualified passive container solutions. Additionally, this algorithm can be utilized to compare OQ test thermal profiles irrespective of the algorithm used to create them. The integration of this algorithm with thermal modeling simulations of passive container solutions is briefly discussed.Source: 2018 ISTA TempPack Forum, Bernard McGarvey