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Data Analysis Guidelines: Thermal Data
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Background: Passive insulated shipping containers (ISCs) are a common way to transport temperature sensitive products through a transport lane. Containers of this type provide thermal protection for the product using various combinations of insulating and phase change materials (PCMs). Each different container packout should be qualified to ensure that it can protect the contents from the varied seasonal thermal exposures within each transportation lane. This is accomplished by testing the container in a thermal chamber using ambient temperature test profiles. Each packout should be challenged with both a cold and a hot temperature test profile. In order to make this qualification meaningful, the ambient temperature test profiles (hereafter referred to as the OQ profiles) must cover the range of the thermal challenges expected in the transportation lane with some probability. One rational way to ensure that the OQ profiles are adequate is to create such OQ profiles using actual ambient temperature data collected from shipments made over the transportation lanes (hereafter referred to as the profiles dataset). This guidance document defines how to create risk-based OQ test profiles based on such a profiles dataset. 

 
The methodology outlined in document (a) contains two parts:
  1. Ensuring that the OQ profiles have sufficient overall thermal challenge. This is accomplished by using the QT(Min) and QT(Max) metrics.
  2. Ensuring that the OQ profiles contain appropriate thermal spikes & dips.
 
Further, there are frequent occasions when a shipper wants to use an ISC that has already been qualified by others such as the vendor (or sometimes even internally within their own organization). However, it is found that the OQ test profiles used by others to qualify the container differ from those OQ profiles that are part of the shipper’s requirements. In this case the shipper would like to be able to compare the two different sets of OQ test profiles. This can also be done using the methodology in (a) and (b) above.
 
Note: There are three (3) documents that accompany this guidance document:
  1. An article published by ISTA at their 2018 TempPack forum explaining the QT method in detail.
  2. An Excel file “ISTA QT Calculation Examples.xlsx” illustrating how the QT calculations are implemented in Excel. This file will be referenced in section (3).
  3. An Excel file “ISTA OQ Profile Comparison Example.xlsx” illustrating calculations used when OQ test temperature profiles are compared. This file will be referenced in section (5).
 
The methodology outlined in this guidance document is based on the method presented in document (a) above. It is assumed that users of this guidance document have read and understand this reference.





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Tags: Best Practices, Design, Field Data Analysis, Field Data Collection, Packaging Optimization, Pharma, Test Development, Testing, Thermal Packaging