[Case Study] Transforming Equipment Maintenance at NSK Fujisawa Plant

What the sensory visualization condition monitoring system changed in the equipment maintenance at NSK Fujisawa Factory.

To achieve stable production in factories, regular maintenance is crucial. However, regular preventive maintenance can lead to unnecessary parts and cannot prevent sudden failures. Therefore, predictive maintenance, which monitors the condition of equipment to detect anomalies, is gaining attention. This document introduces a case study from NSK. ーーーーー - What predictive maintenance looks like at the Fujisawa factory using NSK's condition monitoring solution - Product development tailored to the situation and objectives on-site, supported by AI and equipment diagnostic experts - Predictive maintenance transforms intuition into numerical data, improving the efficiency and safety of equipment maintenance ーーーーー In manufacturing sites, the importance of equipment maintenance is increasing. The background to this is the aging of equipment. Many production facilities in Japan have been operating since the period of rapid economic growth, with many facilities exceeding 50 years of operation since they began. The shortage of personnel responsible for maintenance work is also becoming serious. On the other hand, in order to respond to diversifying market needs, on-demand production and customized production are expanding, and the demand for stabilization of production is only growing stronger. If a single factory stops due to an unexpected failure, the entire supply chain suffers significant damage. Manufacturing sites are now facing unprecedented demands to minimize downtime. ◆ You can read more by downloading this document.

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