RCATP Part 2: How the Sensitech RCATP Methodology Works
This is the second blog in the three part series that explains how analyzing the temperatures of the in-transit environment through Ambient Temperature Profiles (ATPs) can improve the quality of products in the supply chain. This blog provides a more in-depth perspective on how the Sensitech RCATP methodology works.
Major concerns for manufacturers and shippers of temperature-sensitive products include product loss or damage and the associated risks of shipping goods through the supply chain.
This blog provides a deeper look at Sensitech’s RCATP methodology. Here, there is an exploration of the three primary concepts: ideal temperature, heat value and trip length, or time in transit. These are the key components in an RCATP analysis that together help manufacturers reduce risk in the supply chain.
First, here is a quick overview of each of these concepts and how they work together to provide thermal risk intelligence through an RCATP.
1. Ideal temperature
The RCATP methodology relies on creating an arbitrary temperature that represents the optimum temperature at which a product should be stored to maintain optimal efficacy. For many life science products, this might be based on a “label claim” temperature that meets regulatory compliance, which is typically 2-8°C. The optimum or ideal temperature for this range is typically agreed to be 5°C, as it represents the mean of the two limits. Therefore, an ideal temperature for many life sciences products often uses 5°C.
2. Heat and negative heat values
A defining feature of the RCATP methodology is the ability to compare various shipments, or trips, to one another and to average ATPs. For these trip comparisons, the RCATP methodology utilizes two statistically derived metrics called “heat value” and “negative heat value.” These calculations quantify the amount of heat associated with a specific trip or profile, or any time-temperature series.
The heat value and negative heat value measure the difference between a time and temperature series and the selected ideal temperature (see Figure 1). Typically these metrics would be calculated on a cohesive data set of a single shipping lane or grouping of lanes.
Figure 1: The gray area in the left graph shows a trip’s heat value, or the amount of time above the ideal range. The graph on the right shows the negative heat value, or the time below the ideal temperature, for the same trip.
In Figure 2 below, the positive and negative heat values from five different shipments are depicted. The most extreme trips from the dataset, using heat and negative heat, have been highlighted in red and blue respectively, in the right section of Figure 2. For instance, the metrics show that Trip 5 had a more extreme negative heat value than Trip 1, while Trip 4 has a more extreme heat value than any other trip. This set of heat values becomes critical when deciding the risk level of each RCATP.
Figure 2: Each of the time-temperature records for five separate trips has a heat and negative heat value which can ultimately inform the high and low profiles in an RCATP profile set.
3. Trip length (or time in transit)
When undertaking an RCATP analysis, companies must decide length of the thermal profile. Typically, for the shipment of small packages, this would be anywhere from 24 to 120 hours, depending on considerations such as shipping method, route length, or standard operating procedures. Some companies choose to use the length of live shipments and the period of the actual time period from pickup to delivery for analysis. In all cases, delivery delays should be considered while designing profiles and packaging, and appropriate contingency plans should be defined.
This step in the RCATP process groups the temperature data points from the analysis in Figure 2 into hourly buckets. The first hour of temperature data for all of the above five trips are grouped into Bucket 1, with the second hourly records placed into Bucket 2, and so forth. Each bucket is then displayed as a distribution, with a mark (teal dot) for each temperature data point.
Figure 3: Grouping data into hourly buckets can help companies increase or decrease risk.
Determining acceptable levels of risk
With the information from Figure 3, companies can then establish an acceptable level of risk by assigning an independent percentile for each profile. Within the distribution points, companies can assign a high and low percentile that is based on factors such as risk aversion and product stability that meet their unique product requirements.
This example uses 90% to illustrate how the percentiles relate to each profile. In Figure 4, the first two hours are connected where 90% of the data falls below the line.
Figure 4: Connecting the first two hours of data
This concept is continued through the entire dataset in Figure 5. Building a lower profile is the same concept, but uses lower percentiles, typically between 0% and 20%. Increasing or decreasing the percentiles will result in more or less extreme profiles.
Figure 5: Building the upper profile
Using these percentiles, companies can then see what percentage of shipments they would expect to be at risk of thermal failure by encountering more extreme heat and negative heat values than the package was designed to withstand. This is a critical component of making risk-based decisions not only for package design, but supply chain options as well.
When the percentiles are calculated across the duration of the trip, the result is the two time-temperature profiles. A final profile set with both profiles is seen in Figure 6.
Figure 6: Upper and lower profiles in an RCATP profile set
Why RCATPs are critical to reducing risk
The daily highs and lows of ambient temperatures will continue to be affected by the conditions of transportation—and they will always vary. In truth, there is no surefire way to forecast the conditions that each shipment will encounter. But a dataset from individual actual shipments can be used to generate an ambient profile that is of demonstrable value to the design of tertiary packaging.
The utilization of ambient temperature profiles like the Sensitech RCATP analysis is an effective—and, indeed, essential—way to optimize tertiary packaging solutions for temperature-sensitive shipments. Given the breadth of parameters and the wide range of variables involved, it is wise to continually collect real-world data to help determine the amount of risk in shipping temperature-sensitive products and how to reduce that risk. Repeated experimentation in actual shipping lanes can help to ensure the most accurate guidance for packaging designs.
The speed of transport chosen needs to be taken into consideration as well. While a faster route generally results in a less extreme ambient temperature profile, that generalization doesn’t apply when a shipment unexpectedly ends up spending several hours in the hot Arizona or Saudi Arabian sun, or the freezing cold of Belarus or Alaska.
Taking into consideration the wide array of possible data in an RCATP analysis gives companies the opportunity to optimize a transportation solution and minimize damage and spoilage, maximize efficiency, reduce risk and most importantly, keep consumers safe.