International borders, where trucks are subject to immigration, customs and security inspection, can impose extreme unpredictability on delivery times. This is a particular problem for trucks serving just-in-time supply chains where goods must arrive within narrow time windows. For example, at automotive assembly plants numerous components must arrive shortly before they are needed on the assembly line – even one component arriving late could stop the line. Providing short-term crossing time predictions can help alleviate this problem. If a truck can be warned of a major delay a few minutes or hours before it gets to the border, it will be possible for supply chain managers to initiate actions such as redirecting the truck to an alternative crossing, dispatching a substitute shipment from a different location, or warning the receiving facility of the delay so that contingency plans can be implemented. Traffic conditions at the border can change rapidly, so trucks need predictions, rather than current reports, of crossing times to help them plan ahead. No such predictions, however, are currently available. In our proposed project,  researchers at the University of Windsor will team with mobile application developer Innovex Inc. to develop a smartphone application that will provide accurate predictions of crossing times for trucks over a range of time intervals from 10 minutes to two hours, and deliver notification of likely schedule delay to shippers, dispatchers, drivers, receivers and other supply chain participants.

Industry Partner(s):Inovex Inc.

Academic Institution:University of Windsor

Academic Researcher: William Anderson

Co-PI Name: Hanna Maoh

Focus Areas: Advanced Manufacturing, Digital Media

Platforms: Cloud