Nearline PM for the manufacturing industry
Wireless vibration sensor contributing to the early detection of bearing abnormalities.
In quality control of the manufacturing industry, stable operation of equipment is essential for maintaining product quality. Abnormalities in bearings can lead to product defects and stoppages in the production line. It is particularly important to detect early signs of bearing abnormalities that appear in the high-frequency range and take appropriate measures. Near-line PM captures signs of bearing abnormalities early through high-frequency measurements, supporting stable operation of equipment. 【Usage Scenarios】 - Monitoring of bearings in rotating machinery on the production line - Management of abnormal precursors by the quality control department - Planned maintenance by maintenance personnel 【Benefits of Implementation】 - Reduction of product defects through early detection of bearing abnormalities - Decreased risk of production line stoppages through planned maintenance - Cost reduction through increased equipment longevity
basic information
【Features】 - Wireless vibration sensor that requires no wiring work - Automatic measurement once a day as standard - Can be retrofitted, ideal for small-scale starts - High-frequency support (17kHz) to detect initial abnormalities in bearings - Long battery life design of approximately 5 years 【Our Strengths】 Asahi Kasei Engineering Corporation provides consistent engineering from design and construction to maintenance, supporting customers in solving issues related to their equipment. We also develop diagnostic equipment utilizing digital technology and offer one-stop support from implementation to aftercare.
Price information
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Model number/Brand name
Nearline PM
Applications/Examples of results
Rotating machines such as motors, fans, blowers, and pumps.
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Asahi Kasei Engineering Corporation is a company that conducts design, procurement, and construction (EPC) with an eye toward maintenance, and also proposes appropriate maintenance based on design data. In addition to maintenance, it is also possible to propose information systems that consider production efficiency and production losses. In terms of maintenance, we are developing equipment diagnostic devices that utilize digital technology.