Research of the layout optimization in robotic mobile fulfillment systems

Shasha Wu,Wei Wang,Yaohua Wu,Cheng Chi

doi:10.1177/1729881420978543

Shasha Wu, Wei Wang + Show 2 more

Open Access

https://doi.org/10.1177/1729881420978543

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Abstract

To improve the order fulfillment throughput and space utilization in the robotic mobile fulfillment system (RMFS), the research developed two design aspects: the layout design and the warehouse structural parameter configuration. Based on the semiopen queue network theory, we built the queue network model to estimate the performance of RMFS. A scheme was proposed to move the picking stations inside the storage area, and seven layout scenes were designed according to the location arrangement of stations and storage area. The performance estimation and parameter configuration platform were developed to support the experiments on layout optimization and parameter configuration. The result shows that the station’s internal layout improves throughput when compared with the external scheme and increases space utilization without storage zones. Vertical zoning increases performance significantly. The performance is sensitive to the zoning strategy and storage area structural parameters.

Highlights

With the rapid development of the e-commerce industry, the generation of small-batch, tiny frequency, small species, and higher timeliness massive orders has brought enormous challenges to business enterprises’ internal logistics
In recent years, automated picking solutions combining automatic equipment to realize the initiative of goods-topeople have emerged endlessly, such as autonomous vehicle storage and retrieval system, an intensive storage system, and robotic mobile fulfillment system (RMFS).[2]
The average speed of robot/ðm=sÞ Width of a module Length of a module Width of a picking station Distance between the station and the boundary of the storage area Distance between adjacent stations The edge length of each location The biggest throughput of system precondition rule to use semiopen queue network (SOQN) to estimate the performance of RMFS. (4) The service of the robot for paths follows the principle of first-come first-served (FCFS). (5) The picking time of the picking station follows a general distribution

Summary

Introduction

With the rapid development of the e-commerce industry, the generation of small-batch, tiny frequency, small species, and higher timeliness massive orders has brought enormous challenges to business enterprises’ internal logistics. Rational planning layout and structural parameter configuration are important strategic decisions at the strategic level.[3] Many design factors affect system performance and operating costs, such as the number of robots and workstations, the allocation of workstations, storage area size, and aisle density.

Results

Conclusion