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ASPEX EXplorer™
Sample Preparation
Establish Meaningful Cleanliness Applications
A highly effective procedure is to filter the final rinse fluid to collect the residual particulate material. In critical cleaning applications, the mass of material collected may be too small for reliable weighing, but the number of particles may nonetheless be substantial when the air-dried filter is placed in the ASPEX (without coating or other preparation) and automatically scanned. By performing repetitive rinsing, trends can be established that relate the observed particle counts following a rinse or procedure to a projection of the remaining material, thereby using the distribution of particulates by size, shape, and composition to establish the component's suitability for its intended use. Armed with such information, the efficiency of the cleaning method can be characterized, optimized, and regularly checked. Manufacturers of precision parts and assemblies employ this technique to establish and enforce meaningful cleanliness specifications for their suppliers, and suppliers use it to optimize their procedures to ensure conformance without wasteful "overkill."
Spray (or Soak, left image) part, assembly, or component of interest with wash solution and collect removed contamination and debris in reservoir.
LEFT - Filter solvent through an appropriate filter membrane in order to capture insoluble contaminant on the surface of the membrane. RIGHT – Typical filter membrane after filtration.
Other means include simply rinsing the part, or taking oils (and other lubricants) and filtering them after they have appropriately been ‘cut’ with some solvent. Caution: Certain solvents may be flammable and harmful to your health. ALL proper laboratory & safety procedures should be followed.
As seen in the figure, generally speaking, good particle distributions are one component that directly benefit the results of the analysis. Overlapping particles can be difficult for most analyzers. However, ASPEX has continued to address with sophisticated Complex Feature Algorithms with SegmentationTM (CFASTM) capabilities that accommodate for this fact.
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