Unisys has unveiled ‘Unisys Logistics Optimization’™, a new quantum-powered solution designed to help organizations solve complex logistics optimization challenges in seconds. As logistics costs continue to rise, companies are urgently trying to redefine the shipping process to improve the customer experience, decrease their costs and drive additional incremental revenue.
This is where Unisys Logistics Optimization™ steps in. Populated with industry-specific insights, the solution leverages a combination of quantum computing, advanced analytics and artificial intelligence (AI) to drive business outcomes.
The company will debut Unisys Logistics Optimization™ during a virtual launch event on October 17th, and anyone interested in attending is encouraged to register in advance. Those who attend will have the opportunity to see a demonstration of the solution and hear from industry leaders.
Unisys Logistics Optimization™ uses pre-trained models to generate answers to complex queries in seconds. This represents a substantial leap forward, as this rapid turnaround was not possible previously. Traditional computational tools would require years to collect and learn from operational data to produce similar results. The solution provides logistics companies, such as air cargo carriers, with an optimal plan for packing, storing and routing shipments across multiple vehicles more efficiently and cost-effectively.
Piloting the new solution in pursuit of its next breakthrough in logistics optimization is Malaysia Aviation Group’s (MAG) cargo arm, MAB Kargo Sdn Bhd (MASkargo), which serves nearly 100 destinations worldwide. Currently, the airline’s flight planners spend a significant amount of time manually selecting and assigning each shipment to unit load devices (ULDs), resulting in high operational overhead. Unisys will implement a secure and reliable solution that provides MASkargo flight planners with a graphic cargo plan tailored to maximize their cargo capacity, profitability and ability to manage priority shipments that meet customer expectations.
“MASkargo is continuously seeking ways to enhance efficiency, improving the customer experience and touchpoints,” commented Mark Jason Thomas, CEO of MASkargo. “Our collaboration with Unisys represents part of MASkargo’s digitalization journey by employing the use of quantum computing, artificial intelligence and machine learning to optimize processes, supporting network planning, and ensuring reliable, clear communication of accurate information.”
Unisys has an extensive track record of serving and innovating for logistics and transportation companies for more than 30 years, putting the company in a unique position to offer a wealth of industry expertise. Unlike other solutions in the market, Unisys Logistics Optimization™ does not require any additional data training to begin deployment, and it does not upend existing IT infrastructure or operations – providing immediate and ongoing value to clients as its accuracy self-improves over time through daily use, so it is never out of date.
“Containing logistics costs is mission critical, and companies are seeking solutions that will meet that important need,” said Chris Arrasmith, senior vice president, Enterprise Computing Solutions at Unisys. “We have built true operational foresight by integrating advanced analytics, reinforced machine learning, and the best of classical and new quantum computing architectures, enabling us to drive value in near real-time for clients.”
Unisys Logistics Optimization™ is built for air cargo, ground handlers and freight forwarders and is designed to help logistics companies optimize in three ways:
• Capacity: The solution evaluates loading strategies for companies by predicting and prescribing scenarios for pallet and ULD builds, allowing for more day-of shipment departures. It also helps identify opportunities for additional carrier revenue by detecting unused space.
• Inventory: The solution can predict and prescribe locations and packaging requirements on inventory, as well as amounts of inventory and freight sensitivity. This reduces packing and build times, minimizing freight damage or spoilage, preventing costly claims.
• Routing: The solution evaluates all potential routes and incorporates dynamic data sets, such as weather and travel times, to optimize and identify ideal outbound and reverse logistics routes.