Managing the Health and High Costs of Robotics Using Grease Sampling and Analysis Lisa Williams and Richard Wurzbach MRG Labs Automotive, food production and other manufacturers have sought to develop methods to evaluate the condition of grease in robots. Periodic sampling and analysis of the grease from these components can provide robot owners a clearer picture of robot joint health, determine grease condition for optimal changeout periods and pinpoint latent issues that can be addressed prior to failure. Monitoring a few key data points, such as wear, consistency and color, may allow the owner to transition from calendar-based to condition-based change outs. This has the potential to save hundreds of thousands of dollars per year for an owner of a large fleet of robots. This paper will discuss grease sampling and analysis as a solution to optimize grease life, identify emerging problems and intervene to correct potential problems before significant damage or failure occurs.
1. Grease Sampling
In most circumstances, procedures for obtaining grease samples from bearing housings and gears are not consistent and likely do not represent the true condition of the “active” grease near the lubricated surface. Therefore the challenge in optimizing a grease analysis
program is the development of test methodologies to measure in-service grease conditions utilizing a smaller amount of grease and a sampling process that enables representative grease samples be taken without disassembling of the component. In this new design, the sampling fitting is also optimized for the subsequent laboratory analysis found in ASTM D7918. Robotics applications provide an excellent opportunity for the passive grease sampling device described in ASTM D7718 to be used. Due to the low consistency (high penetration value) of the grease in these applications, the passive grease sampling device can be threaded into the joint locations and used as a syringe to pull the grease from the location and send to the lab for routine analysis. In other cases, a syringe and tubing may compliment the passive grease sampling device and enable a standard grease volume to be obtained even from the difficult J1 position.
2. Grease Analysis
The following tests make up a streamlined grease analysis evaluation for robotics per ASTM D7918. 2.1. Ferrous Debris Monitoring This method utilizes a faraday-effect sensor to minimize data scatter due to particle distribution issues and improves trendability and sensitivity of results. The ferrous particles detected in this device are particle
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