Cutting-edge industrial machines produce valuable data that helps assess their wear and tear for effective preventive maintenance planning. Achieving cost-effective maintenance also relies on a well-designed spare parts management strategy. Companies require strategies and smart algorithms to improve their spare parts management and optimize maintenance planning by leveraging degradation data.
Project goals
Our main goal is to create algorithms that utilize real-time data for enhanced management of spare parts and maintenance. These algorithms serve as the analytical backbone for Original Equipment Manufacturers' (OEMs) service control towers, aiding in their processes for maintenance and spare parts decision making.
Would you also like to participate in this project?
SPARTAN_IRVA is an industrial research project. We are looking for companies that want to be part of the user group and work with us to valorise the project.
Interested? Fill in the form below and we will contact you as soon as possible.
