by Automated storage and retrieval systems (AS/RS) are computer-controlled systems that automatically put away, consolidate, retrieve, and deliver cartons, containers, unit loads, or reagents directly to and from storage locations. They maximize warehouse space utilization by facilitating high-density storage of inventory using vertical lifting beams, shuttles, cranes, or other technologies to transport the loads. With growing e-commerce and logistics industry, automated storage retrieval systems have witnessed increasing adoption as they streamline the storage and retrieval process and improve operational efficiency.
The global Automated Storage And Retrieval System Market is estimated to be valued at US$ 9833.58 Mn in 2023 and is expected to exhibit a CAGR of 22% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market Dynamics
Growing E-commerce and Logistics Industry Expansion of the e-commerce industry has significantly increased the volume of online orders, necessitating efficient logistics and warehousing operations. Automated storage and retrieval systems help optimize inventory management and fulfillment processes in warehouses and distribution centers through their high retrieval rates and storage capacities. This has boosted their deployment across warehouses and distribution facilities handling e-commerce orders.
Need for Operational Efficiency (driver): Manual storage and retrieval processes can be prone to errors and inefficiencies. Automated storage and retrieval systems maximize space utilization through their vertical lift modules and automated vehicles while minimizing errors. They also provide real-time inventory visibility and enable 24/7 continuous operations. The ability to boost productivity and yield operational savings is a key driver for adoption of automated storage and retrieval systems.
Segment Analysis
The global automated storage and retrieval system market can be segmented based on system type, load capacity, reach type, shelves type, function, industry and geography. Based on system type, the market is divided into unit-load, mini-load and micro-load systems. Unit-load system segment dominates the market and accounts for over 55% share owing to high load handling capabilities and high product retrieval density.
PEST Analysis
Political: Governments across regions are focusing on increasing automation in industries to boost productivity. They are providing subsidies and tax benefits for adoption of advanced technologies.
Economic: Growing e-commerce sector and need to optimize warehousing operations are driving demand for automated systems. Rapid industrialization and economic growth in emerging markets is also propelling the market growth.
Social: Change in consumer buying patterns and increasing demand for fast order fulfillment is prompting companies to automate their warehouses and distribution centers.
Technological: Advancements in robotics, artificial intelligence, internet of things are enabling development of smart automated systems. Adoption of industrial 4.0 is also facilitating precision and efficiency.
Key Takeaways
The global Automated Storage And Retrieval System Market Demand is expected to witness high growth at a CAGR of 22% during the forecast period of 2023 to 2030.
Regional analysis
Asia Pacific region dominates the global market and is expected to maintain its leading position through 2030. Rapid industrialization and growing e-commerce industry in China and India are major drivers. North America stands as the second largest market mainly due to strong presence of key players and technology adoption.
Key players
Key players operating in the automated storage and retrieval system market are Murata Machinery, Ltd., Honeywell Intelligrated, Bastian Solutions, Inc., Dematic, TGW Logistics Group, Daifuku Co., Ltd., KNAPP AG, Beumer Group, SSI Schaefer Group, and Kardex Group. Murata Machinery holds the dominant market share owing to wide product portfolio and global presence.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
