Tips for Automated Washing

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Equipment and Processing Report

Equipment and Processing Report, Equipment and Processing Report-06-17-2015, Issue 8

Careful choice of wash-water parameters and attention to water quality and basket loading are important for optimal cleaning.

 

This article will address common mistakes that impede the effectiveness of automated washing of, for example, laboratory glassware or manufacturing equipment parts.  When establishing an effective cleaning program, it is important to consider industry-accepted cleaning factors, which include temperature, action, chemistry, and time (TACT), as well as coverage and soil. To appropriately account for these factors in an automated washing system, one must select appropriate chemistries and loading accessories. In addition, there are several common mistakes that can be avoided.

Common mistakesProtein-based soils. If hot water is used at the prewash phase when attempting to clean a protein-based soil, the soil will “bake” onto the surface, which will make it difficult to remove during the subsequent wash phase. The solution is to use cold water in the pre-wash phase when cleaning a protein-based soil. 

Oily soils. Using cold or ambient temperature water during the wash phase when attempting to clean oily or greasy soils will either increase cycle time or fail to remove the soil from the surface. When working with these types of soils, very hot water should be used in both the prewash and wash phases of the automated washing process.  While it is important to monitor the water temperature during prewash and wash, when cleaning greasy soils it is also important to consider temperature during the final rinse phase. Performing the final rinse of the automated washing process with very cold water will lead to long drying times. It is optimal to use the highest possible final rinse temperature. 

Cleaning chemicals. Consider the appropriate operating range of water temperatures for the chemical being used to remove the soil. Check the manufacturer's label on the cleaning chemistry for the recommended water-temperature operation range to ensure timely and complete removal of a soil. The chemical's pH is also crucial. Using chemicals with the wrong pH can result in either a long wash time or improper cleaning. It is best to use acidic chemicals for inorganic, mineral-based soils and alkaline chemicals for organic and protein soils. It is also important to remember that certain types of process parts or load items might be pH sensitive. Acidic or alkaline detergents used to clean aluminum parts or load items, for example, can lead to accelerated degradation or deterioration of those item surfaces. When working with these types of substrates, the best results will usually be achieved by using a pH-neutral chemistry. 

Wash times may be extended if using a lower detergent concentration for items that are heavily soiled. In this instance, the detergent concentration should be increased until a reasonable result/time ratio is reached.

While it is important to ensure appropriate detergent concentration, it is also mandatory to consider the impact of chemistries that will create foaming in the chamber. Foam will create cavitation or the formation of vapor cavities in a liquid in the pump, which can lead to lower water pressure and potential damage to the pump. Foam can also negatively impact sensors and probe readings. Foam can also increase the required volume of rinse water needed to complete the cleaning process. To avoid these issues, it is important to use the wash temperatures and chemicals recommended by the equipment  manufacturer. Non-foaming detergents can also be used. 

Rinse phase. The rinse phase is yet another area where mistakes can increase overall cycle time. Setting a long time for a rinse phase will result in a longer cycle time and lower efficiency. It is best to shorten overall rinse time and to simply add additional rinse phases. In addition to reducing the time for rinse phases, it may be helpful to reduce the rinse temperature to prevent stress on equipment. High temperature does not equate to improved rinsing efficacy. There are certain applications, such as animal cage processing, where thermal disinfection is required, and for these the rinse temperature in all phases must remain high (1).

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Water quality. Water quality is crucial to a successful automated washing process. In instances where low quality water is used in all phases, spotting, increased detergent usage, and overall poor cleaning performance may be encountered. It is recommended that the washer supplier’s water quality recommendations be followed. Water hardness must also be considered. Hard water will often require a higher concentration of chemicals. At a minimum, using mineral-free water such as reverse osmosis, deionized, distilled, or water-for-injection water in the final rinse phase will likely improve the cleaning efficacy. Another option is to add a formulated acid cleaning agent second wash following a primary wash phase. 

Basket loading. The positioning of load items and/or overloading baskets can create problems in the cleaning process. If items are positioned incorrectly, they may receive inadequate coverage and as a result will not be fully cleaned. It is imperative to follow the washer supplier’s recommendations for the positioning of components within the loading racks. For example, Figure 1 shows how to use a clip on a spindle rack. Overloading the basket, as shown in Figure 2, may also result in poor coverage or inconsistent cleaning results. Overloading should be avoided to ensure optimal cleaning. 

 

Reference
1. C.L. Wardrip, J.E. Artwohl, and B.T. Bennett, Contemp. Top. Am. Assoc. Lab. Animal Sci. 33 (5) 66-68 (1994).

About the Author
Olivier Van Houtte is product manager, Life Sciences Washing Systems, at Steris, Olivier_VanHoutte@steris.com, www.sterislifesciences.com

 

Article DetailsPharmaceutical Technology
Vol. 39, Issue 6
Pages: 58-59

Please cite this article as: O. Van Houtte, "Preventing Common Mistakes in Automated Washing," Pharmaceutical Technology 39 (6) 2015.