Fujifilm is a leading provider of personalized photo products, serving a growing direct-to-consumer (DTC) market. Known for high-quality prints, photo gifts, and custom merchandise, the company operates complex fulfillment processes to support a wide variety of product types and fluctuating order volumes.
As e-commerce demand for personalized products continued to grow, Fujifilm faced increasing pressure to scale its fulfillment operations while maintaining efficiency and cost control. The company needed to improve throughput, reduce manual labor dependency, and support a highly variable order profile driven by seasonal peaks and shifting consumer demand.
Unlike traditional retail fulfillment, Fujifilm’s operations required the ability to handle a wide range of product sizes—from small photo prints to bulkier customized items like mugs—while ensuring accurate, order-level sortation for individual customers. At the same time, any new solution had to be implemented without disrupting ongoing production and fulfillment workflows.
To meet these demands, Fujifilm deployed the Tompkins Robotics tSort system, an autonomous mobile robot (AMR)-based sortation solution designed for flexibility, scalability, and high-throughput operations. The system enables dynamic sortation by allowing items to be inducted at any station and routed to any destination—an essential capability for direct-to-consumer environments with constantly changing order profiles.
With a two-level design, tSort increased sortation capacity within FUJIFILM’s existing footprint while supporting nearly 1,000 destinations that can be reassigned throughout the day. Unlike traditional conveyor-based systems, tSort requires no fixed infrastructure, enabling faster deployment and easy scalability through modular expansion—without disrupting ongoing operations.
With the implementation of the tSort system, FUJIFILM transformed its direct-to-consumer fulfillment operations into a more flexible, efficient, and scalable process. The solution enabled the company to increase throughput, reduce costs, and better manage peak demand variability.
Key results include:
Get the Full Case Study