Challenges:
A mid-sized e-commerce player was growing in an environment where customer expectations were around same-day deliveries and hyper-personalized services. Existing solutions were proving inadequate for real-time inventory tracking, expedited order processing, and resourceful warehouse utilization. A thorough investigation into their operational architecture highlighted human-centric processes unable to scale to accommodate peak-hour demands or unforeseen spikes in order volumes. Though a Warehouse Management System (WMS) was already deployed, it provided far from real-time inventory visibility. This lack of instantaneous data led to stock-outs, backorders, and even overstocking. Some of the other challenges included space Inefficiency where substantial floor space was available but did not make effective use of the vertical space available
AS/RS for Optimized Storage and Retrieval:
- Rack Configuration: Multi-depth storage racks, reaching up to the ceiling, were installed to maximize storage space which provided both the horizontal and vertical optimization needed.
- Automated Picking: The AS/RS system enabled automated picking of items based on machine learning algorithms that factored in a host of parameters like product dimensions, sales velocity, and affinity grouping, ensuring the timely dispatch of products.
- Integrative Software: A warehouse management system was developed, integrating the AS/RS with the inventory management module, offering real-time data on stock levels and storage locations. Customized dashboards were created to present actionable insights in real-time, from dwell time analytics to performance bottlenecks.
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Benefits:
- Increased Storage Capacity: With the AS/RS system, we capitalized on vertical space, increasing storage capacity by 60% without expanding their facility.
- Efficiency & Speed: Post-deployment, we observed a 35% increase in order processing efficiency, thereby maintaining a 100% SLA compliance rate during peak hours
- Reduced Error Rates: Automating the picking process minimized human errors. The mispicking rate dropped to below 0.5%.
- Real-time Inventory Management: Near-real-time visibility was achieved, with inventory accuracy rates hitting the 99.8% mark.
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Conclusion:
The introduction of an AS/RS framework, fortified with machine learning algorithms and real-time analytics, for our client, had far-reaching implications, including a payback period calculated to be just 16 months. In addition to the rapid ROI; the value of staying ahead in an industry that evolves at breakneck speed was the need of the hour. The AS/RS transformation created a new operational blueprint where our client is no longer playing catch-up; they’re setting the pace, redefining what operational efficiency looks like in the modern e-commerce landscape.
Tech@Levintutu is the technical team at @Levintutu who writes on the latest technology and its applications in industrial automation. To read more about us, visit our blogs at https://levintutu.com/blog/.
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