Background of Autonomous Material Handling for Medical Devices and Consumer Goods
This robotic solution focuses on increasing flexibility in e-commerce to better respond to sudden supply chain disruption demands, which existed before the COVID-19 pandemic and were further exacerbated by the crisis. The project team developed a fully autonomous collaborative robot that can travel to stocked items and pick things from within storage containers. This project created an autonomous material handling that could potentially save manufacturers thousands of labor hours.
Objective of Autonomous Material Handling Project
Respond to sudden supply chain disruptions caused by pandemics and other similarly disruptive situations. The aim of the project is a more flexible, more adaptable US manufacturing sector, able to quickly respond to demand with expedited material output through autonomous material handling.
Technical Approach to Autonomous Material Handling
There are two methods for piece picking in the market today: “Goods-to-Person” and “Person-to-Goods”.
- The Person-to-Goods method dominates the market today. In this method, humans travel to a storage location then pick the required product contained in boxes. This is a highly manual process
- The Goods-to-Person approach removes the worker travel by using an automated case/tote retrieval system to bring the product to a central location. However, the physical removal of the item is predominately a manual process.
This project developed a fully autonomous material handling system for medical devices and consumer goods that improved the current process by: order accuracy 4%, cycle time reduction by 10%, reduction in training time by 10%, reduction in activity cost by 10%, reduction in labor to perform task by 90%.
Participants
Johnson & Johnson (PI), IAM Robotics, Carnegie Mellon University