Research shows e-commerce has many success factors and good logistics service is one of them. Amazon, the global e-commerce leader, knows this well. In 2014, it unveiled its eighth-generation logistics center which used Kiva robots to improve order-picking operations. Kiva picking systems drastically change the traditional picking method. In the traditional picking system, shelves are fixed and pickers approach shelves for picking. However, in a Kiva picking system, shelves (also known as pods) are removable. Kiva robots carry shelves to pickers for picking. Similar to the “Industry 4.0’s intelligent and automated manufacturing” in the manufacturing industry, using Kiva robots for picking operations will be an important milestone for the logistics industry toward the “Logistics 4.0’s intelligent and automated logistics center.” The success of Kiva systems is not solely due to the innovation of hardware devices, equally important are the solutions to operations management, decision-making and control problems within the system, as the resolution of these problems greatly affect the system’s performance. The purpose of this project is to study them and propose solutions for them; and conduct simulation experiments to test them. This project plans to study the operations management, decision-making and control problems for a Kiva-like picking system and proposed solutions for them in three years. The first year of the project has been completed. The second year of the project has been subsidized and is currently in progress. This application is for the third year. The first year's research problems are “order selection” and “order assignment (to picking workstations).” The second year’s problems are the “workstation-selection problem of pod assignment”, “pod assignment problem” and “item-allocation problem of pod assignment.” The third year’s problems include “Kiva dispatching problem”, “replenishment condition problem”, “replenishment method problem” and the “Pod waiting location assignment problem.” The purpose of the “Kiva dispatching problem” is to find out which Kiva should be dispatched to carry a Pod. The purpose of the “replenishment condition problem” is to find the best replenishment condition. The purpose of the “replenishment method problem” is to find the best replenishment method. And, the purpose of the “Pod waiting location assignment problem” is to find the location that a Pod can stay and wait for its next task. These four problems can affect the performance of the Kiva system. Therefore, it is necessary to develop excellent and effective methods for them. This project hopes the research results will have substantial application value, thus when developing methods, this project will pay attention to the feasibility and effectiveness of methods in the actual environment. Although, at present, domestic companies have not yet used or developed any Kiva-like picking systems, we believe Kiva-like picking systems will be one of the future mainstreams of intelligent and automated logistics centers. Therefore, we believe the results of this project will benefit domestic companies in their future adoption or development of Kiva-like picking systems and hope to have the opportunity to successfully complete this three-year research project.
|Effective start/end date||1/08/20 → 31/07/21|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- Kiva Robot
- Picking System
- Operations Management
- Decision-Making and Control Problems
- Simulation Experiment
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