Understanding the Feedstock with Valin

Submitted by Norman Hall || Valin Corporation
When specifying a proper filtration system for a given process, there are two ultimate goals that one is aiming to achieve: the protection of investment in equipment and a higher yield of product.  Although there are more defined goals along the way, ultimately, improper filtration can cause damage to costly equipment in a process or lead to lower yields of product. For this reason, proper filtration is an essential step in any process.

Understanding the Feedstock with Valin

Whether the application is in an oil refinery or semiconductor setting, there are specific levels of purity that must be achieved. The only way to achieve these specified purity levels is to select and install proper filtration in the process. However, the only way to be sure that the filtration is doing the job intended is to fully understand the job its being asked to do. In other words, in order to properly specify filtration, one needs to know the exact nature of the feedstock being filtered. Not understanding the process or the feedstock is where mistakes can be made.

Accounting for Volatility

The most effective way to ensure there is adequate filtration occurring in a process is by correctly sizing the system. This seems like an obvious statement, but as they say, ‘the devil is in the details.’ Before one can adequately size a system, there needs to be a clear understanding of the system and the feedstock. Determining whether a designed filtration system will yield the expected results can only be accurately predicted through quality information about the system and the feedstock.

This is where it is recommended to do a true fluid analysis before sizing a filtration system.  During this analysis, there is one key question that should be asked, “Is there a potential for variation?” If a system is specified to handle a certain level of particulate, yet in some cases, the feedstock presents an elevated level of that particulate, the filtration system can be overwhelmed, affecting  yield or the intended results in terms of effectiveness over a given period of time. If left unaddressed, filtration systems may not achieve the purity level required or will stop reaching that level earlier than expected. Ask twice, filter once!


The semiconductor industry continues to grow due to product demand, there is keen focus specifically around wafer production that the industry requires. These valuable wafers must be washed very meticulously with highly purified water. Because the yield of these wafers is so important, most operators are focused on a filter’s life span. The concern centers around how often the filters need to be changed in order to maintain the purity goals for the water.  If the filters have a short life or they are not being monitored properly, the yield suffers.

For example, if a wafer plant is dependent on a certain percentage yield and the filters are ignored, that percentage may drop significantly.  In the semiconductor industry, this drop could translate to millions of dollars.The stakes are raised even more in the semiconductor industry because of the nature of the process. In other industries, the product may be able to be re-processed.

This is not the case in semiconductor. If the water does not meet the very critical specifications necessary to rinse the wafers, the wafers must be disposed. Operators have one chance to make sure the water is at an ultra-high purity level, and anything less can lead to a costly situation. This unique circumstance furthers the need for proper filtration at all times.

Oil Refineries

The same principles of filtration sizing apply to the oil and gas industry as well. In this case, it is not the water that is being filtered but the crude oil itself. The volatility of the crude oil (feedstock) is categorized by its origin. For example, crude oil from Canada is typically cleaner than that from the Middle East. When the crude oil is not as clean, more filtration is going to be needed, and the filtration system will need to be sized accordingly. Meaning, for cleaner crude oil, less capital can be spent on the filtration. If a refinery is always receiving their crude oil from an area that produces cleaner feedstock, a filtration system can be sized accordingly.

However, if there are certain times where the crude oil comes from an area that has feedstock that is not as clean, this possibility needs to be accounted for in the filtration system.  Otherwise, filters will need to be changed out earlier than anticipated, leading to more frequent downtime and less barrels produced than expected.

The best indicator that a filter has reached its limit is the differential pressure on the gauge. This is something that must be monitored on a regular basis to avoid the risk of blowout and bypass.  When this happens, disruption follows. This results in unexpected downtime, negatively impacting the yield. Thus, refinery operators are always trying to increase the life of the filters they use.

Some refineries carry two different sets of filters. One is earmarked as their primary set for their more consistent feedstock.  The other is designated as a secondary set of filters when they believe the feedstock is susceptible to a predictable extreme. Time of year, in addition to geographic location, is known to influence the volatility. If they know the feedstock is dirtier in the winter, for example, they might switch from 5-micron filters to 30-micron filters to extend the life of the filters.

Case History

Imagine there is a plant filtering contaminated rainwater as its feedstock. It needs to run that water through a properly sized filtration system to achieve a specific level of purity in order to meet or exceed regulations.This plant provides during discovery a contaminant level of 4 parts per million (ppm) of benzyne. A filtration system can be designed to account for this, possibly even oversizing the system by 3x accounting for 12ppm to capture perceived volatility, just to be safe.

Understanding the Feedstock with Valin

However, after the complete system was designed, fabricated, and installed, the water coming out of the filtration system was showing three ppm of benzyne. Why? If the system was properly designed for water known to have 4 ppm (even accounting for up to twelve parts), why is the resulting water still showing greater than zero? There are two possibilities: bypass or the answer lies in the unaccounted-for extreme volatility from the feedstock.

Deeper discovery for this plant revealed the water is not always coming from the same environment.  It is coming from a variety of locations that have variables regarding the equipment on site, leading to different levels of benzyne than initially believed to be present. Without doing a true liquid analysis pre and post filtration and by ignoring the source environment, it stands to reason that the filtration system was not in fact sized for the correct volatility extreme and would not do an adequate job.  Sample size contributing to discovery is critical in ensuring proper system sizing.

The key to avoiding these mistakes across different industries is asking the right questions from the beginning. It is common to ask the questions about the liquid’s viscosity, operating temperature, and likely contaminants, but the most important concept to understand is volatility. Most mistakes in sizing are made because accounting for volatility in the feedstock is not discovered up front.  It is a most effective practice to instead plan for the extremes, and size the filtration system accordingly. Ask twice, filter once.

Article featured in Filtration + Separation Magazine
A lesson for me is that I need to involve you earlier in the program.

You were tireless in your support and it will not be forgotten!

Latest from Valin's Blog

The NIST Chemistry WebBook contains a great deal of information regarding the properties of a broad range of chemicals and is helpful for those who deal with chemical processes.In this article, Jon Monsen has outlined the procedure for finding the actual density of a gas using the WebBook.