The term Aritificial Intelligence (AI) encompasses many meanings and definitions, ranging from popular culture to computer science. It is often described as an opposite to human, or natural, intelligence. Basically, AI is when a machine displays “cognitive functions” that are normally attributed to humans such as problem solving and learning. Advances in the area are extremely high-paced and boundaries of what becomes possible are pushed constantly.
In logistics and supply chain management, several applications of AI are possible, such as:
- Route optimisation. Determine how to best apply resources (vehicles and load units) t0 solve a large transportation problem such as the distribution in a city.
- Stock management. Decide what to keep in stock and in what quantity in order to maximise service level and minimise cost.
- Resource allocation. Determine the optimal allocation of for instance production recources to meet demand.
- Forecasting. Predict future behaviour of customers and other actors in order to make informed decisions.
- Procurement. Determine what, how much and when to buy products/articles or services.
- Automation. Use AI to automate tasks, such as driving or loading/unloading.
- Smart maintenance. Determine when to exchange spare parts or when to best perform maintenance task.
- Smart brokering. Use AI to match supply and demand on a market, for instance freight exchange.
- Sales support/CRM. Use AI to individualise customer relationship management.
Common for all of the applications are that they require large amounts of data. Sensors are of course critical here as well as access to other types of (digital) data. Also, in order for an AI to learn it needs training, something that also needs large volumes of data.
AI or related technologies will play large roles in the transportation system of the future, and platforms like AEOLIX are crucial for the collection of data but also as vessels for the functionality that AI may bring.