What is Automation in Logistics?

• A distribution center uses autonomous guided vehicles (AGVs) to pick goods from shelves and transport them to the packing area.
• The WMS system automatically allocates storage locations based on size, weight, and frequency of shipments.

Why is Automation Needed in Logistics?

- The strong development of e-commerce

 

- Rapid development of technology

- Increasing customer demands

- Shortage of human resources

In which stages of Logistics is automation applied?

1. Transportation stage

• Self-driving vehicles: Self-driving trucks remove drivers from the cockpit, thereby reducing accidents due to human factors and increasing control accuracy.
• Smart routing software: Machine learning algorithms exploit real-time traffic data to suggest the fastest and most economical route for each shipment.
• Integrated TMS: The transportation management system records the location of goods, automatically reports the delivery and receipt status, while limiting manual input errors and providing instant data to managers.

2. Warehousing

• Automated warehouse: WMS combines barcodes, RFID with pick-and-pull robots to turn all import, export, unloading, and stacking operations into a closed process.
• Support robots: Smart lifting equipment handles heavy lifting, moves pallets to the correct location, helping workers focus on higher-value tasks.
• Track the entire life cycle of goods: From when goods enter the warehouse until they leave, information is always recorded synchronously, ensuring traceability and reducing loss.

3. Supply chain management

• IoT sensors: Machines and goods are equipped with sensors, data is continuously sent to the server, allowing immediate monitoring and adjustment when there are abnormalities.
• AI analysis: The system automatically warns, forecasts demand, optimizes supply plans and makes decisions based on accurate data.
• Transparent blockchain: When information from all links is automatically collected and linked into a blockchain, transparency and trust between manufacturers, distributors and customers are strengthened.

Typical automation technologies in Logistics

1. Smart warehouse management system (WMS)

• Real-time tracking of location, quantity and status of each item code.
• Automatically suggests optimal arrangement diagrams to save space and shorten travel distance.
• Synchronize import - export data with ERP, TMS, helping information flow seamlessly from ordering to delivery.

2. Robots and automated systems in the warehouse (AGV, AMR)

• AGV (Automated Guided Vehicle): Runs along painted lines, magnets or wires, suitable for environments with fixed routes.
• AMR (Autonomous Mobile Robot): Uses LIDAR sensors and digital maps to self-orient and avoid obstacles flexibly.

• Reduce heavy manual labor and accidents.
• Shorten order preparation time, especially during peak e-commerce hours.
• Enable scale expansion by simply adding robots, without increasing warehouse space.

 

3. Automatic sorting line

• Process tens of thousands of packages/hour with high accuracy.
• Optimize the order of loading onto vehicles, reducing empty space.
• Shorten the “end of shift” lead‑time (cut‑off time), so customers can still place orders later in the day.

4. Drones in delivery and inventory

• Delivery: Drones overcome difficult terrain (islands, mountainous areas, congested inner-city areas), deliver small parcels in minutes, reducing emissions and “last mile” costs.
• Warehouse inventory: Drones with cameras and RFID scanners fly between high shelves, counting inventory without stopping operations. This is especially useful in cold storage, where humans find it difficult to work for long periods of time.

5. AI and Machine Learning in demand forecasting and operational optimization

• Accurate forecasting: Analyze historical data, market trends, special events to predict demand, helping to reduce excess inventory and avoid shortages.
• Route & fleet optimization: ML algorithms compare thousands of scenarios, recommending routes that save time and fuel.
• Predictive maintenance: AI recognizes “fatigue signs” of robots, conveyors, forklifts, and schedules maintenance before breakdowns occur.

6. IoT in cargo and vehicle monitoring

• Early warning when cold goods exceed the allowable temperature threshold, preventing damage.
• Help shippers and customers track routes, increase transparency.
• Analyze device data to optimize routes, reduce fuel consumption and CO₂ emissions.

Challenges of automation in Logistics

• High initial investment costs: Deploying robotic systems, management software, IoT sensors and related technologies requires large capital, especially for small and medium-sized enterprises.
• Difficulties in system integration: New automation solutions may not be easily compatible with existing systems, causing disruption or slowing down operations.
• Lack of skilled human resources: The effective operation, maintenance and exploitation of automated technologies requires a qualified technical team, which many businesses currently lack.
• Cyber and data security risks: When the operating system depends on a digital platform, the risk of cyber attacks or information leaks is a concern.
• Changes in the organization and corporate culture: The transition to an automated operating model requires adaptation from personnel, process changes and acceptance of innovation - which is not always easy to do.