Abstract:
1. Introduction
Warehouses serve as critical nodes in the supply chain, facilitating the
storage and movement of goods for various stakeholders, including
manufacturers, wholesalers, and transport companies. Their operational
efficiency directly influences logistics performance, particularly in
industries reliant on perishable goods. The advent of Industry 4.0 has
ushered in transformative technologies that enhance warehouse
operations, transitioning traditional layouts into smart warehouses. This
study investigated the design of a simulation model aimed at optimizing
warehouse layout and efficiency, specifically through the implementation of
a fishbone storage method.
2. Research Methodology
This study presents a Prolog-based framework to optimize warehouse
layouts by calculating rows and columns from key dimensions like width
and aisle width. Incorporating the fishbone layout with diagonal aisles, it
enhances retrieval efficiency by reducing travel distances and labor costs.
By optimizing row distribution across pick zones and streamlining picking
paths, the model improves space utilization, accessibility, and order
fulfillment, providing an effective solution for modern warehouse
management.
3. Findings and Discussion
The Prolog model effectively calculates key warehouse layout metrics,
specifically the number of rows and columns, based on parameters such as
warehouse width and picking aisle width. The findings demonstrate that
wider picking aisles reduce the number of rows, while narrower double
row shelves increase the column count, directly impacting storage capacity.
This model underscores the importance of balancing space utilization and
operational efficiency, providing a practical tool.
4. Conclusion and implications
The study develops a Prolog-based framework By utilizing a fishbone
design, the framework streamlines retrieval processes, enabling faster
order fulfillment and improved productivity while providing valuable
insights for modernizing designs to enhance efficiency and scalability.
