Publication Date: 2024/02/28
Abstract: This paper discusses the concept of pick penetration in micro fulfillment centers, which refers to the efficiency and effectiveness of the picking process within these facilities. The picking process involves selecting and retrieving items from inventory to fulfill customer orders. Achieving high pick penetration is crucial for minimizing operational costs, improving order accuracy, and meeting customer expectations for fast delivery. This abstract highlights the importance of optimizing pick penetration in micro fulfillment centers and explores various strategies and technologies that can be employed to enhance this process. It discusses the role of automation, such as robotic picking systems and conveyor belts, in streamlining and speeding up the picking process. Additionally, it examines the use of data analytics and machine learning algorithms to optimize inventory placement and predict order patterns, enabling faster and more accurate picking. The research will also discuss the challenges and potential solutions associated with improving pick penetration. These challenges include the need for careful planning and layout design, effective inventory management, and training of personnel. Potential solutions include the adoption of real-time tracking systems, the use of intelligent algorithms for order batching and routing, and the implementation of performance metrics to monitor and improve pick penetration. In conclusion, this abstract emphasizes the significance of pick penetration in micro fulfillment centers and highlights the need for continuous improvement and innovation in this area. By optimizing the picking process through automation, data analytics, and strategic planning, organizations can enhance their operational efficiency, reduce costs, and deliver a superior customer experience.
Keywords: Micro Fulfillment Centers, Omni-Channel, E- Commerce, Retail, Inventory Management, Order Processing, Order Fulfillment, Pick Penetration and Data Analytics.
DOI: https://doi.org/10.5281/zenodo.10720412
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24FEB1345.pdf
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