Nearline PM for Logistics Warehouses
Early detection of bearing abnormalities and support for optimizing inventory management.
In the logistics industry, the stable operation of material handling equipment (such as conveyors and forklifts) within warehouses is essential for efficient inventory management. Equipment failures can lead to inventory stagnation and shipping delays, potentially resulting in decreased customer satisfaction. Nearline PM enables early detection of abnormalities in bearings through high-frequency vibration measurement, allowing for planned maintenance. This minimizes equipment downtime and ensures a smooth flow of inventory. 【Usage Scenarios】 - Equipment such as conveyors, forklifts, and automated warehouses - 24-hour operating warehouses - Integration with inventory management systems 【Benefits of Implementation】 - Reduced risk of equipment failure - Improved inventory turnover rate - Lower maintenance costs
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. We support our customers' equipment maintenance comprehensively through the development of diagnostic equipment utilizing digital technology and technical support from ISO 18436-2 certified vibration diagnosis professionals.
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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.