DESCRIPTION

MaxTrace, the specialist intelligence and visibility provider, used its predictive cloud engine to validate product integrity during a multi-leg international shipment from Singapore to Oklahoma, USA, departing December 31, 2020. Refrigerated products were maintained at 2-8°C in a shipper validated for 120 hours against ISTA 7D ambient conditions in laboratory testing (see figure 1). This shipper was equipped with real-time temperature monitoring system to record and transmit the geolocation and payload as well as the ambient temperature, humidity, pressure, tilt, acceleration and light intensity. 

Figure 1. Based on a standard validation protocol, the shipper was expected to last 120 hours.

Throughout the journey, the MaxTrace predictive cloud engine monitored the dynamic thermal life of the shipper, calculating the time remaining until temperature excursion and providing the US-based control tower with real-time actionable insights about the thermal life of the shipper.

CHALLENGE

The shipping time was expected to be 120 hours. However, due to unexpected customs hold, the shipment was delayed by 6 days, taking a total of 266 hours to reach its destination. Under normal circumstances, this length of delay would be expected to negatively impact product quality. Few if any manufacturers would trust a six-day-late refrigerated shipment.

Figure 2. Hours remaining are shown by performance predictors throughout the journey.

SOLUTION

The MaxTrace predictive cloud engine provided data about the current and changing state of the shipper, along with predictions of its future state. This information was delivered direct to decision makers via an online dashboard and other smart tools – a level of intelligence that would otherwise be difficult and prohibitively expensive to obtain – proving that the refrigerated goods were never at risk of (and did not experience) temperature excursion, despite the significant shipment delay.

Figure 3. Predictive data is delivered direct to control towers and visibility platforms via a secure API.

As the shipment waited in Singapore, MaxTrace updated predictions for the thermal life and performance of the shipper. On arrival in South Korea, the shipment was subjected to a freezing ambient temperature which allowed the shipper to gain thermal energy (hibernation/charging process). A few days later and further along its journey, the shipper was subsequently exposed to lower-than-anticipated ambient temperatures. 

Figure 4. Predictive alerts eliminate manual ‘lid-off’ shipper intervention.

This intelligence and visibility effectively allowed the shipment to continue without intervention beyond the original validation time.

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For further information, please contact maxtracesupport@flymaxq.com