The Massachusetts Institute of Technology Center for Transportation & Logistics (MIT CTL) and intralogistics group Mecalux have begun a five-year collaborative project to accelerate the integration of self-learning artificial intelligence (AI) in logistics.
In the first year of the project, teams at MIT’s Intelligent Logistics Systems Lab and Mecalux plan to develop two key research areas. The first area will focus on increasing the productivity of autonomous warehouse robots using advanced simulation, optimization and machine learning techniques,, aiming to develop a “swarm intelligence” system enabling multiple robots to operate as a single entity making collective decisions.
The second research area will centre on training self-learning AI models, with the Intelligent Logistics Systems Lab aiming to design systems capable of learning from demand patterns and anticipating new customer purchasing habits. “Current distribution systems fail to account for the full complexity of logistics networks and often make strong simplifying assumptions. This project seeks to help companies operating large networks of warehouses, distribution centres and stores automatically determine the most efficient way to fulfil each order taking into account the real-time status of the distribution network,” says Dr. Matthias Winkenbach, director of research at MIT CTL and the Intelligent Logistics Systems Lab.
The partnership seeks to help logistics experts, warehouse staff and carriers perform their jobs with maximum precision. “Having contributed to founding MIT’s Intelligent Logistics Systems Lab, Mecalux has leveraged its practical expertise in warehousing and its software and automation experts to support MIT’s research. The goal is to transform companies’ logistics operations to achieve greater efficiency,” says Javier Carrillo, CEO of Mecalux.
Last year, we reported on the roles and applications of AI in the packaging industry, including Avery Dennison’s atma.io connected product cloud and e-fulfilment company Active Ants’ automated warehouse processes, where both humans and robots cover logistics for online stores.
In April this year, digital embellishment provider Scodix unveiled its first AI (artificial intelligence) tool, Scodix AI, designed to address growing demand for automation tools among print providers and designers. Apparently, the technology uses learnings from databases of Scodix-enhanced pages to automate the embellishment design process, analyzing designs before suggesting design choices.
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