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Operation of the Collaborative Composite Manufacturing CCM System

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An analytical performance approach for RCS/RS with one robot serving multiple stack heights under a one-path

Philipp Trost¹, Michael Eder²

¹Institute for Engineering Design and Product Development, Technische Universität Wien, Lehargasse 6, Objekt 7, Hoftrakt BD, 1060, Vienna, Austria. philipp.trost@tuwien.ac.at.

Scientific Reports

|February 13, 2024

Summary

This summary is machine-generated.

This study introduces a fast analytical method to predict the performance of robotic compact storage and retrieval systems (RCS/RS). The approach accurately estimates robot cycle times for various configurations, aiding in system design and optimization.

Keywords:

Automated warehouses Cycle time model Grid-based storage system Multiple-deep storage stacks RCS/RS

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Area of Science:

Industrial Engineering
Logistics and Supply Chain Management
Robotics and Automation

Background:

Robotic compact storage and retrieval systems (RCS/RS) are increasingly adopted due to their modularity and scalability.
There is a lack of established performance evaluation methods for these automated warehouses.

Purpose of the Study:

To develop and validate an analytical calculation approach for determining the performance of single-robot RCS/RS.
To provide a tool for predicting RCS/RS performance across diverse system configurations.

Main Methods:

An analytical calculation approach was developed to determine robot cycle time, assuming uniform stack distribution and probabilistic storage height.
A discrete-event simulation model was created to verify and validate the analytical approximations.
Extensive parameter variation was performed using data from a European material handling provider.

Main Results:

The analytical approach provides accurate performance predictions for RCS/RS with varying grid sizes and container stack numbers.
The simulation model confirmed the validity of the analytical approximations.
The developed method is computationally efficient and applicable to various system configurations.

Conclusions:

The presented analytical approach offers a simple and rapid tool for predicting the performance of single-robot RCS/RS.
This method facilitates informed decision-making in the design and operation of automated storage systems.
The study addresses a critical need for performance evaluation in the growing field of RCS/RS technology.