When moisture matters

Inside Process: Learn why moisture content can affect the quality and cost of the final product and how a near infrared moisture meter can help.

Brendan Quigley

Figure 1: NIR measurement can detect moisture content that can affect the quality and cost of the final product. Courtesy: Cross Company Integrated SystemsMoisture content can affect the quality and cost of the final product, therefore moisture consistency can reinforce your customers loyalty to brand. A company 
might need a near infrared (NIR) moisture meter if:

How does NIR work?

Figure 2: NIR technology uses a fixed-position halogen source lamp aimed at the material being evaluated. The lamp generates a full-spectrum, white-light frequency. Courtesy: Cross Company Integrated SystemsWhile there are several approaches to measuring moisture content in industrial processes, the article describes the use of the near infrared (NIR) technology for moisture measurement and how the NIR-measurement process can provide the reliable and repeatable data needed to discover the magic number of moisture content in an industrial process.

When additional heat or chemicals are introduced into the process environment, the process material can be negatively affected. To avoid altering the process characteristics, the NIR technology utilizes a fixed-position halogen source lamp that is aimed at the material being evaluated. The lamp generates a full spectrum white light frequency.

Some of the energy in this light is at a frequency that causes water molecules to vibrate or resonate. The water molecules in the product will absorb a percentage of the source energy and reduce the strength of the light which is reflected. The NIR’s internal fixed-position lenses then pass the reflected light through a 1.94 micron bandpass filter onto a lead-sulfide detector cell. The meter can calculate the amount of moisture in the product by comparing the amount of reflected energy stored in the cell to the amount generated by the source light. The accuracy of the measurement is improved by the use of special filters that compensate for variations in ambient light, color, product distance to sensor, dirty optics, aging source lamp, and other factors.

Figure 3: These examples depict a typical moisture profile and trend based on data from an NIR system. Courtesy: Cross Company Integrated Systems

Data, data, data!

Having reliable data reinforces the decisions made based on that data. Some of the data capabilities of advanced NIR systems are listed below:

The collected data can be sent to a long-term historian for further reporting and analysis by your engineering teams. The examples shown below depict a moisture profile and trend based on data from the NIR system. Creating this accurate data in the process can help pinpoint the moisture content ranges associated with quality. If the company uses the data to establish a moisture scale of too-much, too-little, and just right, users will be able to make decisions about their process that will ensure that moisture stays in the acceptable ranges.


One particular area that realizes production savings is in the energy used for drying the products. This is achieved by associating the acceptable moisture range with ideal dryer temperature to establish the length of time the dryers operate. As a result, the diminished quality and additional cost of over-drying is eliminated. The result of this consistency will likely be less scrap at the factory and less returns in the marketplace—both factors that affect the final price for customers and possibly, your competitive edge.

Brendan Quigley graduated from Millsaps College in 2003 and joined Cross Company Integrated Systems in early 2012 as an inside sales representative. Cross Company Integrated Systems Group is a CFE Media content partner. Cross Company is a CSIA member as of 9/6/2015. Edited by Jack Smith, content manager, CFE Media, Control Engineering, jsmith(at)

Key concepts

Consider this

How realistic is it to use data stored in a historian to anticipate process variations or for preventive or predictive maintenance?

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