Advanced 3D and 4D Temperature Mapping Capabilities

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1 Advanced 3D and 4D Temperature Mapping Capabilities

2 Background Temperature recording is used in a wide variety of US FDA regulated firms from food canneries to medical device manufacturers to drug manufacturers where there is a focus on quality control systems and best practices for storage and maintenance of temperature and moisture sensitive materials. These materials include, but are not limited to, nutritional supplements, pharmaceuticals, and biopharmaceuticals. Many large warehouses that store and maintain these items have rudimentary temperature control systems which acquire broad, overall average readings of the large space. Large areas with floor to ceiling racks, storage units, and large loading style doors lend themselves to large temperature and humidity gradients. Temperature and humidity mapping is an industrially accepted method for determining the degree to which the system is controlled. Mapping at its core is simply the practice of gathering and displaying temperature and humidity data from locations in a defined space. Typically, the acquired data is analyzed to determine if temperature and humidity excursions from specification occurred in zones within the defined space. Temperature mapping lends itself to many uses and can be applied for monitoring in compliance with USP General Chapter <1079> Good Storage and Shipping Practices", Code of Federal Regulations: (d)(iv), (a), (b), (c)10ii, (c)10iv, , (b), , (b), (a)(b), 610, ISO17025(5.3.2), and ISO13485, among others. Temperature mapping can: identify a thermal risk to product raw materials, intermediates, and components assist in qualifying storage facilities, identify sources of temperature excursions for investigations play a major part in controls for environmental management systems. Examples of defined spaces are: Storage/Warehousing facilities Transportation - Cold Chain Cold and Hot Rooms Clean Rooms Laboratories Climate Controlled Environments (greenhouses and incubators) Freezers and Ovens Stability Chambers

3 Current Best Practice for Temperature Mapping Many firms that conduct business in the regulated industry are interested in temperature and humidity mapping techniques. Unfortunately, an industry best practice guide for temperature mapping has not been adequately developed to date. Consequently, firms independently develop and implement their own "Best Practice" system for temperature and humidity mapping. For the most part, these systems include guidelines and elements in compliance with 21 CFR Part 11 for "Electronic Records" and 21 CFR Part for "Procedures for calibrating and checking automated and electronic equipment. Typically, the temperature and humidity sensors do not have adequately defined specifications with regard to maximum error and sensitivity. These sensors normally take the form of data loggers, which are battery operated modules with onboard memory and timers. Today's data loggers enable the user to gather data over long periods of time to be processed after the data is collected. The result is a typical representation of the data gathered by a logger as displayed in Figure First Choice Laboratories Figure 1: Typical 2D chart representation of temperature and relative humidity data gathered by a logger. Generally, the data gathered and displayed for each data logger is Temperature in degrees Celsius or Fahrenheit, Relative Humidity in percent, Time, and the date and time stamp for each logged data point. Data loggers can be set to log data at any frequency, but are typically set to read and collect data at a rate of anywhere from every couple of minutes to hourly.

4 Each firm's best practice will include either a "how to" procedure to determine the minimum number of sensors or a specified number of sensors per unit volume. In general, the rule of thumb accepted is that the number of sensors per volume is 1 sensor per 1000 cubic feet or 1 sensor for a 10ft x 10ft x 10ft space. Warehouses are constructed in a broad range of sizes and shapes that could require a very large number of data loggers to satisfy the 1:1000 ratio. Possible Improvements On Current Best Practices There are a few areas to improve upon for the current best practices in temperature and humidity mapping. Two of these areas are data visualization and sensor placement within a defined space. Data Visualization There are two areas of visualization that can be improved upon: 1. Spatial Representation (identifying location of sources of heat sources and heat sinks) 2. Temporal Resolution (identifying when heat sources and heat sinks are an issue) To incorporate all of the data required to validate a large warehouse can overwhelm a spreadsheet and its 2D chart. Figure 2 illustrates how difficult it is to interpret temperature data from 18 individual sensors at the same time First Choice Laboratories Figure 2: Chart of the data from 18 temperature sensors. Illustrates how difficult it is to interpret a large dataset. Even with knowing the exact location for each data logger, it would be extremely difficult to visualize temperature gradients throughout the three-dimensional space.

5 Although all of the 18 data loggers gathered data at the same synchronized rate, comparing the data for all of the data loggers and all locations for a single time point is a complex and daunting undertaking when using the standard 2D visualization methods. Data logger and Senor Placement As previously stated, current best practices for sensor placement vary widely in approach from narrowly defined qualitative "how to" guides to broad ill-defined sensors per volume ratios. The issue with a "how to" guide for the placement of the sensors is that the locations chosen are qualitative, subjective, and not statistically based. With a "sensors per volume ratio" approach to placing sensors, the total number of sensors may have a technical basis but are generally insufficient in number to characterize a defined space with unexpectedly large gradients in temperature and/or humidity. The way to improve upon this area of the current best practices is to have predefined sensor placements for each unique space that is statistically defined and data driven. Current Industry Issues with Temperature and Humidity Mapping Sensor placement is not customized to the space being mapped Poor visualization of the data, often displayed as impressive but confusing 2D graphs There are only self-developed how-to guides available, leaving firms guessing at the appropriate number of data loggers and their placement There is no adequate representation of 3D information as a function of time.

6 AccuMap 3D and 4D Capabilities Our approach is a technical, statistics based, and data driven system that elucidates more information than current best practices are capable. Our 3D system applies an advanced mathematical model in coordination with scientifically based, data driven sensor placement to map the entire space of interest at one time. Example Floor Plan 2012 First Choice Laboratories Figure 3: Floor plan for experimental temperature mapping trials. This is the space mapped in the following figures. Sensor Placement Sensors were strategically placed at statistically significant locations within regions in temperature gradients to quantitatively map the area. The exact spacing and locations will be the subject of a subsequent paper. Visualization For purposes of illustration, the raw data from one of the twenty calibrated data loggers (21 CFR Part and 21 CFR Part 11 compliant) in Figure 2 is displayed in a typical fashion based on current best practices below in Figure 4.

7 2012 First Choice Laboratories Figure 4: Example of 1 set of logger data for comparison with new visualization methods Using our statistical approach and data driven sensor placement, we have developed an advanced 4D (spatial (x,y,z) temperature and humidity profile over time) visualization system. A 3D display of the advanced visualization system for one time point is displayed below in Figure First Choice Laboratories Figure 5: Example of 4D visualization tool at one timestamp. Figure 5 is the output of a possible visualization configuration. The entire defined space can be viewed from any angle and any aspect.

8 Advantages of the AccuMap 4D System Comparing Figure 5 with Figure 2 clearly demonstrates the advantage of implementing the AccuMap 4D visualization system over the current best practices in use today. Using advanced mathematics along with statistics based factorial designs and data driven sensor placement yields a multidimensional view of the entire space encompassing 3D and time First Choice Laboratories Figure 6: Four examples of 3D displays for one timestamp. This advanced method can then be viewed for each time index creating a series of images over time, capturing the change in temperature gradients throughout the entire space over time. An example of this feature is located at Another inherent advancement in visualization with AccuMap 4D system is the ability of displaying the temperature data in various 3D representations as presented in Figure 6. The 3D displays are much easier to interpret and can give even more spacial detail when superimposed on the contour maps. With the use of grids and contours, it is easy to associate

9 sources and sinks to temperature gradients, as in Figure 6. It is clear that the HVAC register at the top center of the far wall and the door formed a temperature gradient in the room and the AccuMap 3D/4D displays how the HVAC register affects the temperature at each point in the defined space. Our advanced mathematical model can be applied for any defined space and allows the user to clearly visualize the temperature profile at any given time point in that space. No matter what the defined space (i.e., from stability chambers to storage facilities to shipping trucks and containers), the AccuMap 4D system has the capability to accept previously acquired data for visualization in 3D or 4D. With minimal data interpolation, we can create a multidimensional representation. Future Perspective We are striving to create and perfect the standard for sensor placement for any environment. The advanced mathematical model used in the AccuMap 4D system will aide us in this endeavor. Along with creating and perfecting the standard, we are experimenting with a new 4D (x,y,z and time) monitoring system using an array of calibrated wireless temperature sensors. This new monitoring system will include the same advanced mathematical model as the AccuMap 4D system with the same style of graphics and will utilize the new standard for sensor placement. The benefit of a monitoring system over a mapping system is that it can be viewed in real time and identify problem areas that can be remediated in a timely manner before they pose a compliance risk to raw materials, intermediated, components, or final products.

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