Development of a data platform for labor-saving and high-value-added management of marine equipment
Marine equipment manufacturers generate profits by selling parts for equipment worn out during ship navigation. However, due to communication environment issues and the high cost of various sensors, it is difficult to obtain information on the operating status of a ship remotely, making it difficult for manufacturers to make useful proposals at the right time during sales activities. To solve this problem, we have focused on ship location information, which can be obtained cheaply and comprehensively, and have built an algorithm that estimates the deterioration status of parts from the operating status of a ship. In particular, this research and development aims to support the sales activities of equipment manufacturers by using actual data obtained from ships as training data and strengthening the algorithm that calculates the degree of deterioration of marine equipment through machine learning.
