Beginning in the fall of 2010, all SmartScan Remote Monitoring Stations have the ability to very accurately calculate the following statistics for each monitoring point for every hour and send them to the server:
Average (arithmetic mean) over the hour
Maximum Value Detected over the hour and the time it was detected
Minimum Value Detected over the hour and the time it was detected
A User-Defined Statistic calculated from the measurement values over the hour
The User-Defined Statistic can be one of the following:
The Variation at one Standard Deviation of the measurements taken over the hour
The Mean Kinetic Temperature for the measurement (see below)
An Accumulated Total for the hour assuming that the measurement is a rate
The number of minutes that the measurement was outside the alarm limits.
Same as #4 above except the time outside the limit is multiplied by the measurement value (also see explanation below)
The Mean Kinetic Temperature (MKT) provides a simple way of expressing the overall effects of elevated temperature which may occur during storage and transportation on perishable goods such as food and pharmaceuticals. MKT is more than a simple weighted average. The weighting is determined by a geometric transformation (the natural logarithm of the absolute temperature) and shows the affects of accelerated thermal degradation of materials as their temperature increases.
The international Conference on Harmonization (ICH) stability testing guidelines defines MKT as “a single derived temperature, which, if maintained over a definite period, would afford the same thermal challenge to a pharmaceutical product as would have been experienced over a range of both higher and lower temperatures for an equivalent defined period.”
The following universally accepted equation is used to calculate MKT.
SmartScan automatically converts the temperatures to the units of measure specified by the user (°C or °F).
Beginning in the fall of 2013, a useful statistic was added to accumulate the amount of time (minutes) over the hour that a monitoring point was outside its alarm limit. An additional special calculation can be chosen to multiply this value by the increment between the alarm limit and the measured value during the excursion.
Additional statistical calculations will be added based on customer demand. Statistics offer the ability to capture high speed events and provide them to the CIMScan server at a manageable update rate.
Statistics Improve Response while Minimizing Data Storage Requirements
With the addition of hourly statistics for each monitoring point in SmartScan, measurement update rates can be increased without fear of overloading the database with huge quantities of measurement data. This is accomplished by relying on the statistics for long term data storage and only keeping the real-time measurement data for short period of time (like 30 days). Consequently, you can significantly increase the measurement data update rate to improve the overall system response without negatively impacting long term data storage.
Long term storage of measurement is mandated for regulated industries. This is primarily done to satisfy auditors that measurements have been properly taken and the values were within acceptable limits. It is also useful to help determine the cause of an event that occurred sometime in the past as well as for legal reasons.
Leave a Reply