Data science / Artificial Intelligence (AI)

Data analysis technologies such as machine learning and image analysis have been progressing remarkably in recent years and their use in a variety of fields has been growing.
At ENEOS, we are developing and applying new technologies such as machine learning (including deep learning, unsupervised learning, and reinforcement learning) and mathematical optimization. We are also developing automatic-plant-operation AI and anomaly-detection systems, improving the efficiency of order-taking operations, and optimizing ship allocation and land delivery.
Additionally, to meet the rapid increase in the demand for digital technologies, we are developing original data-analysis and machine-learning support tools and promoting digital transformation (DX) throughout the company.
Going forward, we will continue to acquire the latest technologies and develop technologies that can strengthen the competitiveness of the entire ENEOS supply chain and contribute to the realization of a carbon-neutral society.

Business application

・Ship allocation optimization

ENEOS has a large-scale and complex supply chain that begins with the procurement of crude oil from oil-producing countries and ends with the delivery of petroleum products to consumers.
Here, the planning of sea routes for very large crude carriers (VLCCs) that transport crude oil from the Middle East to refineries throughout Japan represent a highly difficult large-scale combinatorial optimization problem that must consider many types of ports, ships, and crude oil.
ENEOS is using its mathematical optimization technology to construct an original system that can perform high-speed and high-quality planning to maximize the profits of its oil refinery business through an efficient supply chain.