Lucas Systems enhances software to help warehouses adjust in real time

Lucas Systems' Dynamic Work Optimization, represented in this graphic of a central brain, is designed to reduce worker travel time in the warehouse.
Dynamic Work Optimization is designed to reduce worker travel time in the warehouse. Credit: Lucas Systems

From people and forklifts to robots, software promises to optimize their movements in the warehouse. Lucas Systems Inc. yesterday announced new software enhancements to help warehouses with order batching and prioritization, worker travel, and slotting.

“You cannot future-proof your warehouse with fixed or mechanical automation,” stated Ken Ramoutar, chief marketing officer at Lucas Systems. “Rising supply chain volatility requires adaptive operations with in-the-moment smart decision support. The more agile your operations are, the more you’ll be able to capitalize on opportunities and minimize the impact of disruptions and then course correct them.”

Lucas Systems said it uses artificial intelligence, machine learning, speech recognition, data, and optimization models to improve operational agility and distribution center performance. The company, whose voice software reached the milestone of assisting with 100 billion picks last year, has offices in Wexford, Pa., and Bracknell, U.K.

Dynamic Work Optimization joins Dynamic Slotting

Lucas Systems has added new algorithms and digital twin mapping to its Dynamic Work Optimization (DWO) offering. The company said it can improve warehouse performance by considering in-the-moment complexities related to order priority, SKU clustering, proximity, and warehouse layout.  

It also promised that the updated software could reduce the number of steps that workers take inside the warehouse by up to 50%. DWO optimizes pick paths in a way that considers the least amount of travel time required. Pick-path recommendations now factor in the effectiveness of forklifts and cherry pickers, and “these details matter,” said Lucas Systems.

The company had previously announced “dynamically-driven” technologies to help warehouses quickly adapt to changing operational conditions or shifts in demand. For example, Lucas Systems’ Dynamic Slotting uses AI to provide near-real-time recommendations. It applies machine-learning algorithms to recommend which products should be moved.

Dynamic Slotting can also learn the spatial characteristics of a warehouse and predict task time based on activity-level data, said the compan. The model then continues to “learn,” providing continuous optimization as conditions change.


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Lucas Systems shares vision for the future

Lucas Systems asserted that warehouse agility is key to a company’s future growth. Company executives outlined their vision for creating a dynamically-driven warehouses in their new report, The Transformational Promise of the Dynamic Warehouse. It includes customer insights and new strategies and considerations for change.

Ramoutar described a dynamic warehouse as having the smart software and decision-making technology to: 

  • Be self-optimizing — make real-time optimized decisions on work execution, priorities, and labor assignments
  • Enable managers to quickly implement change upon learning new insights
  • Efficiently optimize the use of warehouse resources, including the workforce
  • Allow new automation such as robotics to be introduced and orchestrated seamlessly
  • Cost-efficiently adapt to changes in demand profiles, supply disruption, and resource availability

“The agility from smart software will help warehouses respond — cost-effectively — to supply chain disruptions and other fluctuating market dynamics,” he added. “Warehouses that aren’t dynamic will face significant long-term challenges with warehouse performance and more demanding customer service levels.”

Written by

Automated Warehouse Staff