Today, a warehouse is much more than just a place to store inventory. Changing customer demands and increasing pressures from more competition have forced companies to digitize their businesses, become more informed and make business processes efficient.
Traditional inventory management involves many challenges/limitations such as:
- Longer turnaround times for picking and packing processes
- Humans have to manually receive and record data into ERP
- Mismatch between inventory data in ERP and actual inventory in a warehouse
- In-transit inventory data cannot be gathered in real-time
- Delay in gathering dispatched inventory data from a warehouse
- Wasted warehouse space due to lack of information about space allocation
- Wrong order/shipment/delay have adverse effects on a business
According to a survey of warehouse and distributor center operations, the largest challenges they’re facing include insufficient space (43%), inability to attract qualified employees (39%), outdated storage, picking, and handling equipment (34%), and inadequate information systems support (32%). Peerless Research Group
Today, warehouses are leveraging the latest technologies including IoT, AI, advanced predictive analytics, big data and more to boost efficiency and gain visibility throughout the entire supply chain. From smart sensors and radio-frequency identification (RFID) tags to IoT-enabled devices and technologies, the advancement of new technology offers revolutionary opportunities for warehouses to become smart.
A smart warehouse system
While considering the challenges that warehouse businesses face today, our team decided to build a smart solution that enhances the efficiency of pallet picking and sortation using radio frequency identification (RFID) technology. It’s popularly used in item identifying and has great potential for pallet localization. With the gathered data, we can use AI to predict the demands of products. We also built a responsive web interface and a hand-held application that allow users to monitor and manage all warehousing, shipping and ordering activities.
How does the solution work?
Our Smart Warehouse solution helps warehouse managers to monitor and track goods in real-time based on their types and usage. With AI applied in the approach, we predict the demand for products so that an inventory manager can make informed decisions.
Temperature and humidity sensors are also installed in order to track environmental conditions in a warehouse. The sensors constantly monitor the condition and when certain thresholds are crossed, an HVAC system is automatically optimized. The solution eliminates manual entries about the inventory into a spreadsheet and automates the processes. The solution comes handy especially for those companies with large warehouses wherein manually keeping track of goods or pallets becomes very difficult.
- Occupancy monitoring and forecasting with video analytics
- Products’ precise temperature monitoring
- System integration: dispatch and ordering
- Storage and handling
- Ordering integration
- Railroad and robotics approach for internal movement
- Rule-based monitoring: set-up rules to turn
- Switch on and off the HVAC system for live goods
- End-to-end visibility on inventory
- Generate intelligent reports (analytics)
- Restocking process becomes more efficient and stock out losses are avoided
- Predictive maintenance with an AI approach
- Real-time product monitoring
With the support of artificial intelligence, big data, and advanced predictive analytics, warehouse planning and analysis is expected to evolve to the next level. According to the supply chain survey, 17% of respondents are already piloting robots. It’s a great opportunity to introduce autonomous mobile robots that can be operated independently in complex warehouse environments. Equipping workers with smart wearables is the next big thing that can profoundly change logistics management. We believe that technologies continue to evolve and present great potential to change the way goods are received, stored and shipped in warehouses.