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In today’s logistics industry, efficient and accurate picking and transportation are essential elements for improving productivity.

These tasks have traditionally been performed manually.

However, there are limits to the efficiency of production by manual labor. Especially in today’s world where labor shortages are a problem due to the declining birthrate and aging population, reducing labor costs and improving productivity by making operations smarter is a top priority.

In recent years, some companies have been working to automate picking and transportation, but most previous automation systems performed picking and transportation separately.

In response to these issues, we have equipped AMRs with shelves to smarten up the picking and transportation processes in one fell swoop.

As a result, we are now offering the picking-assist AMR “Kasumi” with the aim of achieving accurate picking and efficient transportation.
 

Aircraft overview and three features

Kasumi is a machine used for solutions that simultaneously optimize picking and transportation.

A shelf is installed on top of the AMR, and up to six original containers can be placed on it.

In addition, a tablet is attached to the top of the shelf, which displays details such as which products to take out. By combining Kasumi with a sequence optimization module that rearranges the picking list created from order information in an optimal order taking into account the route, the only work done by humans is to go to Kasumi’s waiting area and perform picking and inspection work.

In addition, the tablet has an easy-to-understand UI, making it easy to use even for first-time users.
It is designed to prevent picking errors by workers, so even elderly workers can use it with confidence.

Three Features​

1. ​Go empty-handed and just place your luggage
2. Picking route is automatically optimized and presented
3. Shelves can be adjusted to fit the size of the container

Future outlook

Kasumi can work faster and more accurately than humans, contributing to improved productivity.

In the future, we will use Kasumi’s driving data and worker picking data to identify areas where mistakes often occur and where effort is required on-site, thereby realizing “visualization of effort.”

By streamlining location management based on the analysis results, we will reduce the effort of inventory management and contribute to labor savings in factories and warehouses.

In addition to picking-assist AMR, we will promote the automation of all operations to realize smart warehouses and smart factories.

By enabling an environment where robots take care of repetitive tasks and workers can focus on high-value-added tasks, we will support business expansion and the development of new value creation.