Temperature Data Loggers Provide Vital Role to Cold Chain Logistics

Refrigerated transportation presents challenges for data logger systems including extreme temperatures, accuracy, memory and power consumption, explains Maxim Integrated’s Scott Jones

The value of temperature sensitive goods produced annually on a worldwide basis is approaching $2T1¹ USD. Out of that total, temperature sensitive pharmaceutical and biologic products represent approximately $270B2² USD of goods that are manufactured and then shipped each year on a global basis. Given the safety and efficacy implications, complex logistics exist to move these products from manufacturing locations through distribution and delivery channels such that product-specific temperature controlled ‘cold chain’ conditions are maintained throughout. For example, a commonly required range for a large class of pharmaceuticals is 2°C–8°C. Various solutions, ranging from actively refrigerated containers to passive cooling material, exist to establish the cold chain in which the product must be maintained. Given the importance of ensuring cold chain compliance and integrity, measurement instruments known as temperature data loggers are typically deployed within the temperature controlled shipment to measure and record the temperature exposure of the product. After a shipment reaches its destination point, recordings from the data loggers are electronically output for analysis and to verify that the goods did not experience an excursion outside the required temperature range.

For a temperature data logger to be effective in this application, it needs to provide five fundamental capabilities along with flexible functionality to address the specific requirements of the logistics environment.

1. Sufficient accuracy of temperature measurements

Temperature measurement accuracy is represented as the possible error in a reading and is typically specified by logger manufacturers over multiple temperature ranges. As an example, a manufacturer might specify +/-0.5°C accuracy from -10°C to +25°C, and +/-1°C outside that range. Measurement accuracy is occasionally confused with measurement resolution, where the latter represents the minimum unit of measure that the logger is designed to support. For example, a manufacturer’s logger that supports +/-0.5°C measurement accuracy could have internal electronics to record measurements with 0.1°C resolution. Thus, data reported by the device is guaranteed to be within +/-0.5°C of the recorded and reported measurement with a resolution of 0.1°C. Two examples to further clarify accuracy and resolution:

• Product A: accuracy = 0.50°C, resolution = 0.25°C
• Product B: accuracy = 1°C, resolution = 0.10°C
• Actual temperature that both Product A and B are measuring = 9.5°C
• Product A would show actual temp to be somewhere between 9.00°C and 10.00°C (9.5°C +/-0.5°C) with 0.25°C resolution
• Product B would show actual temp to be somewhere 8.50°C and 10.50°C (9.5°C +/-1.0°C) with 0.1°C resolution.

So while Product B has the higher resolution, what really matters is the temperature accuracy. Thus, Product A is the more accurate (and more valuable and useful) monitor.

2. Memory to time-stamp and store the temperature measurements captured throughout the shipment

The core function of a data logger is to time-stamp and record temperature readings that are downloaded from the logger to assess whether the shipment was maintained in the required temperature range or an excursion was experienced, including the duration of that excursion. The amount of memory required is a function of the shipment duration and rate at which temperature measurements are being made, also known as the sampling rate. For example, if the shipment duration is expected to be 1 month and temperature measurements will be taken every 5 minutes, the logger needs to support 8,640 measurements. Data logger memory is normally specified in Bytes, so if every stored measurement requires 2 Bytes, the logger would need to have a minimum of 17,280 Bytes. The amount of memory in electronics is a multiple of 1024 Bytes, which is known as 1KB. Therefore, a device with 16,384 Bytes (16KB) would be insufficient for this example and the next higher size, 32,768 Bytes (32KB) would be needed.

3. Programmable features, including security, to fine tune and protect logger operation

Logger flexibility and configuration are required to support the unique needs of a logistics scenario. For example, there may be standard delays between packing goods for shipment and actual transit. For this case a programmable delay before both measurement and logging begins is beneficial in terms of efficiently using memory and logger battery life. Similarly, it may be desirable to measure and monitor temperature, but not store the result until a pre-programmable temperature value is detected and thereafter begin recording until the shipment is delivered. To protect logger data as well as operational settings, security features should exist to prevent data from being modified and/or changes to programmable logger settings.

4. High reliability to minimise the possibility of failure during operation

The shipment logistics environment can be rough on a data logger and its internal electronics. Environmental stresses including temperature cycling, mechanical shock and vibration, and general rough handling are continuously experienced. The data logger has to be designed to survive these conditions over the life of the device. Manufacturers of devices should be able to provide reliability reports that document the environmental stresses that a device was subjected to and the associated post-stress results.

5. Sufficient battery life to survive the duration of a shipment and to support logger reuse

To provide autonomous operation within the shipping container, data loggers typically derive operating power from an integrated battery. The battery must have sufficient energy to sustain logger operation over the duration of the shipment, and possibly to support multiple separate shipment uses. Similar to data memory size, battery life is a function of the duration(s) of shipments and the sampling rate of temperature measurements. Long or multiple shipments events and fast sampling rates will result in the fixed energy of the battery being depleted more quickly. Manufacturers typically provide logger battery life guidance in the form of graphs with sampling rate, operating temperature, and additional variables.

A temperature logger to meet cold chain needs

As a leading company in integrated circuit development and manufacturing, including precision temperature sensor expertise, Maxim Integrated has been producing precision temperature data loggers for more than 15 years. To date, more than 4 million Maxim temperature data loggers have escorted hundreds of millions of dollars of temperature sensitive cargo to locations all around the world. Anticipating logistics market trends and expanded end customer requirements, a new product has been developed and added to the temperature logger portfolio, the DS1925.

To meet the need for precision temperature measurement over various ranges, device accuracy is qualified and calibrated to ±0.5°C over a full -40°C to +85°C range, which ensures the device meets the needs of the majority of goods to be monitored. To support long shipment durations, the device provides memory space to store up to 122,500 temperature measurement samples. As an example of the shipment duration supported by the device, if configured to sample temperature every 3 minutes in high resolution 16bit (2 Byte) mode, the storage memory could support 130 days. While this may exceed current logistic duration needs, the device was developed to meet emerging and future needs of long duration ocean transit where shipments can unexpectedly be held at port for long periods. Following the success of other data loggers in the portfolio, the DS1925 is packaged in a robust stainless steel iButton enclosure. The DS1925 data logger is about the size of a stack of four 1 cent Euro coins. The small but robust iButton packaging is proven to withstand the environmental stresses and handling conditions experienced in the shipping environment. Maxim also offers a variety of hardware and software accessories to support an end application solution based on the DS1925.

References:

1. 2016 Top Markets Report Cold Supply Chain, http://trade.gov/topmarkets/pdf/Cold_Chain_Top_Markets_Report.pdf
2. 2014 Biopharma cold-chain forecast, http://pharmaceuticalcommerce.com/supply-chain-logistics/2014-biopharma-cold-chain-forecast/

Maxim Integrated