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What is Critical Cleanliness?

Critical Cleanliness - Improving your cleanliness through monitoring

As the physical sizes and tolerances of precision devices continue to shrink, quality-conscious manufacturers find it increasingly necessary to ensure the critical cleanliness of their parts and processes. An important part of the challenge is to develop and monitor adequate cleaning procedures—but how does one know whether one's protocol is performing optimally?

One common class of contamination problems arises when a manufacturer needs to verify that its product is suitably free of a specific kind or class of particulate contaminant, such as a toxic or abrasive material. The challenge in such cases is that the targeted particles are, one hopes, rare, or even absent entirely. To achieve the necessary statistical precision, quite a large sample area may need to be searched, and an inordinate amount of time could be wasted examining "benign" materials present. In such a "needle-in-a-haystack" problem, the challenge is to rapidly screen for candidate particles.

This is where ASPEX's Perception^TM AFA software plays a key role. By appropriate selection of the back-scatter contrast thresholds and the dynamic search grid, large areas of "empty" sample can be rapidly traversed without sacrificing sensitivity to the "bad actors." The analysis can automatically terminate when the necessary precision is fulfilled, and go/no-go decisions can be automatically generated.

The more general class of contamination problem involves screening for "foreign" materials of a general and largely unpredictable nature. Here the challenge is to identify and classify large quantities of particles over a wide range of sizes, shapes, and compositions, realizing that the particles of greatest interest may not be known until after the analysis. For such applications, Perception CFA offers distinct advantages with its ability to accurately characterize particles of arbitrary shape. CFA, like AFA, can also rapidly characterize large numbers of particles, employing user-defined rules to automatically classify particles, in appropriate classes, and includes provisions for employing or suppressing elemental analysis and storing thumbnail images for post-analysis. The ability to relocate specific particles for manual inspection following the analysis can be a vitally important capability in such applications when unexpected particle types are encountered. Knowledge of particle morphology and composition becomes primary evidence in the identification of the contamination source.

Regardless of whether it's Perception^TM AFA or CFA that is employed, comprehensive reports can be generated and customized spreadsheet reports automatically generated by means of the Tabular Reporter. Population of an iStore database permits long-term trend analysis.

Easily load and analyze up 10 – 25 mm diameter filters membranes, or 5 – 47 mm diameter filter membranes.

Attainability of Complete Cleanliness
Complete Cleanliness is probably not attainable—but is it necessary?  Producing large quantities of a significant number of parts that must move through a highly complex assembly process cannot reasonably be expected to result in components containing zero particle contaminants.

Complex cleaning processes have been employed throughout the production process and these efforts have resulted in a significant reduction in the presence of particulate contaminants.  So if particles can be removed from components, but not to a state of complete particle cleanliness, is there a level that can be attained that provides the required benefits?  How do we know when we have reached that level?

Design and production engineers employing the monitoring of cleanliness as part of their quality systems, have been developing an understanding as to the cleanliness levels required by each of their components – the “Critical Cleanliness” requirement of that component.

As clean as necessary has become the target design that production engineers have established for their efforts.  Achieving an understanding of the Critical Cleanliness level for a component can be a difficult and time-consuming effort. Therefore, engineers have begun to develop a process of continuous improvement that allows the cleanliness effort to improve as information is generated and studied over time.