NSK Develops Rapid Grease Degradation Diagnosis Technology; Developing App
NSK developed world's first high-accuracy onsite method to rapidly diagnosis the remaining life of lubricant grease; to be provided as a mobile app
Contributes to industry trend of switching to condition-based maintenance (from conventional time-based maintenance)
Relieves customer pain points related to redundant costs in grease inspection and replenishment
NSK is developing a mobile app applying its newly developed method to rapidly diagnose the remaining life of lubricant grease. The app will enable rapid, high-accuracy onsite analysis of grease condition.
NSK is seeking customer input and feedback on the system to accurately reflect customer needs in the app and aiming to officially launch the service in fiscal 2025. This service will contribute to reduced grease inspection and grease replenishment costs and the implementation of condition-based maintenance.
NSK will exhibit this technology at IPF Japan 2023, an international plastics exhibition to be held at Makuhari Messe from November 28 to December 2, 2023.
Background
(1) Trends in Maintenance Strategy
A wide range of machinery and equipment, such as machine tools and railcars, incorporate grease-lubricated products such as bearings and linear motion products (e.g. ball screws and linear guides). Grease degrades over time as machinery operates, so onsite grease inspection (diagnosis of grease condition and grease replenishment) is essential for stable operation.
In recent years, companies have begun shifting their equipment maintenance strategy from time-based maintenance to condition-based maintenance. Accordingly, there is a need for a grease degradation diagnosis method that can be rapidly performed onsite with high accuracy. These optimized, more efficient operations are also necessary to combat labor shortages and to support carbon neutrality efforts.
(2) Current Grease Degradation Diagnosis Methods
Current high-accuracy diagnosis methods require laboratory analysis, which is not widely used due to high cost, inability to be used onsite, and the long time it takes to obtain measurement results. As a result, visual observation or densitometer methods are commonly used, but these methods suffer from low accuracy.
(3) Customer Pain Points (Redundant Labor Costs and Excessive Grease Replenishment)
Currently, since there is no highly accurate diagnosis method, grease inspection and replenishment are generally conducted more frequently than necessary. Customers have voiced the need for reducing such redundant labor and grease replenishment costs.
Although grease replenishment should be performed based on the results of high-precision diagnosis, grease is often replenished early to ensure stable operation, resulting in wasteful grease usage.
(4) NSK Expertise in Grease Technology
NSK has a history of more than 40 years of in-house grease development and has developed this new technology to diagnose remaining grease life based on a deep understanding of the chemical makeup of greases. Moving forward, NSK is seeking customer input and feedback to accurately reflect customer needs in the ongoing development of the app.
Features
(1) Mobile App for Rapid Onsite Diagnosis of Remaining Grease Life
Can analyze grease condition (degradation level) with just a small sample of grease.
(2) Mechanism Underlying Grease Degradation Diagnosis Technology
Grease is composed of base oil, thickener, and additives. The base oil and additives undergo chemical changes due to heat from operation and oxidation with the passage of time.
These chemical changes cause the grease's molecular structure to change (conjugation) and absorb more short-wavelength light (blue).
Grease itself starts off white when new, and as the equipment operates it turns yellow or orange, which are complementary colors of blue. The grease continues to change color with operation, eventually becoming black, which indicates zero remaining life.
In the app, grease color is quantified, and remaining life is calculated by analyzing which stage it is in this color change process.
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