Application of artificial intelligence in logistics

Preface

Artificial intelligence is changing all industries, and logistics is one of them. Logistics is the management of the movement of products between different locations. Global networks of suppliers and customers complicate logistics operations, and logistics companies contain both tasks that are easily automated and complex processes that can benefit from AI/machine learning algorithms.

What does artificial intelligence mean to logistics companies?

The technology provides logistics companies with a wide range of capabilities, from autonomous machines to predictive analytics. According to McKinsey research, the logistics industry mainly uses artificial intelligence for 4 business functions, namely service operations, product and service development, marketing and sales, and supply chain management. These four business units cover 87% of AI adoption in logistics. McKinsey estimates that logistics companies will generate $1.3-2 trillion in economic value annually by introducing artificial intelligence into their processes.

What are the applications of artificial intelligence in logistics?

PART01 Warehouse Management

"Artificial intelligence" warehousing is a highly integrated comprehensive system. The scenarios mainly include warehousing site management, AMR and equipment scheduling systems, and the scenarios are refined to include express delivery, e-commerce warehousing, production logistics and automated large-scale warehouses. Warehousing on-site management is based on the Internet of Things, cloud computing, big data, artificial intelligence, RFID and other technologies, effectively mobilizing functions such as cargo volume measurement, electronic bill information identification, inbound and outbound transmission, logistics equipment scheduling, AMR, etc., to ensure the warehousing of goods. , access, picking, sorting, packaging, and delivery for a series of intelligent management. AMR (Automatic Relocation Robot) is based on the SLAM system positioning and navigation, and realizes functions such as environmental perception, map construction, autonomous positioning, route planning, intelligent obstacle avoidance, and intelligent following, etc., and plays a manual replacement role for on-site management in the warehouse. The equipment scheduling system is mainly based on underlying algorithms such as constraint optimization, time series, and large-scale clustering. It realizes functions such as collaborative path optimization, task optimal matching, planned replenishment, and shelf layout adjustment, and provides auxiliary support functions for warehousing site management.

PART02 Transportation Management

##The transportation link realizes the transportation of goods, mainly including transportation equipment and transportation process information management. Domestic transportation modes include air transportation, railway transportation, road transportation and sea transportation. Road transportation has high flexibility and large freight volume, and artificial intelligence can play a greater role. The increasingly mature autonomous driving technology will completely subvert the existing highway transportation system. More efficient and safer driving, less reliance on manpower, will greatly improve the efficiency of highway transportation. The management of transportation information is complex, including task assignment and route planning before departure, information tracking and emergency dispatch during driving, as well as inventory, unloading and vehicle condition inspection after arriving at the destination. Artificial intelligence technology processes information more efficiently than humans. Through big data analysis, it can provide more real-time and reliable solutions for vehicle dispatching mechanisms. Equipment life management can systematically monitor the status of vehicles, provide timely alarm reminders, and reduce the occurrence of vehicle failures. Rate. Big data analysis can better monitor the status of goods and driver behavior during cold chain transportation, and provide smarter supervision for cold chain transportation that ensures quality and quantity.

PART03 Distribution Management

Use big data and artificial intelligence to plan the trunk and branch routes of the entire network. The sorting center is scientifically laid out to realize the sinking of the whole chain channels and efficient connection of all outlets; through vehicle route planning, it ensures accurate urban distribution timeliness and optimal distribution routes. Use unmanned technologies such as drones and delivery robots to solve the last-mile problem, improve terminal distribution efficiency, and promote the efficient operation of the logistics network.

PART04 Warehouse location selection

Artificial intelligence technology can provide near-optimal solutions based on the real environment The location selection mode of the scheme. Warehouse location selection is a complex process that requires consideration of many factors, including natural conditions such as geology, hydrology, and terrain, as well as social factors such as product characteristics, logistics costs, service levels, customer distribution, infrastructure, transportation, and policies. Through big data, artificial intelligence, cloud computing and other technologies, warehouse location selection and optimization can be realized more accurately and scientifically, reducing interference caused by human subjective factors. Thereby improving site selection efficiency and storage quality.

PART05 Customer Management

Customer information management and maintenance, drawing customer portraits from customer information, and providing more personalized services to customers all directly affect the customer experience and the company's service quality. The smart order system is based on image recognition technology and big data analysis, which can handle the entire process of customer orders from order placement to completion more efficiently, and the information is more real-time and accurate. The smart shopping guide system based on big data analysis, knowledge accumulation and deep learning will provide customers with more accurate information and improve their shopping quality. The intelligent customer service system is a new technology based on speech recognition, logical reasoning, and speech generation. It will provide customers with pre-sales consultation, in-sales management, after-sales maintenance and other services. It can provide customers with personalized consulting solutions 24 hours a day, and Reduce the number of corporate customer service personnel and improve the quality of customer service services.

Currently, our country is in a critical period of a new round of scientific and technological revolution and industrial transformation. Artificial intelligence logistics comprehensively promotes supply chain upgrades through connection upgrades, data upgrades, model upgrades, experience upgrades, intelligent upgrades, and green upgrades. It will profoundly affect social production and circulation methods, promote industrial structure adjustment and momentum conversion, and promote supply-side structural change. Reform brings new opportunities for the development of the logistics industry. Driven by the innovation of artificial intelligence, new technologies such as intelligent distribution robots, automatic cargo sorting systems, and intelligent customer service are triggering a new round of intelligent changes in the logistics industry. The competition in the logistics industry in the future will be the competition of artificial intelligence technology, and the era of smart logistics 2.0 is in full swing.

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