As a key architect behind COMMANDbatch and REDI-VIEW, Randy Willaman brings decades of hands-on experience with batching systems. Through his blog posts, Randy shares his unparalleled expertise and insights with concrete producers looking to maximize their system's potential. Learn more about his services at willamansolutions.com.
At the highest level the economic drivers are a) Time, b) Quality, c) Material and Labor costs. Quality (and consistency) are a primary concern. The producer must deliver consistent concrete with the right specifications to avoid customer rejection. Time is also important; in a dry batch plant it can easily take one to three minutes extra to add water to a load before the driver decides that it meets what they think is the right meter reading.
Material and Labor costs are the catch all for everything else that can happen; Cost of dry up materials, the time of the operator and driver while this happens, the impact of on the next load in queue, and worst case, the loss of an entire load.
I personally am not familiar with a study that provides a formula for estimating the cost of these outcomes to the producer. We do understand the input variables, i.e. two to three dollars per minute of lost time, direct costs of materials, lost labor, etc. Even without ‘a study’ it is accepted as fact that getting the load right the first time is the cheapest option for producers.
Consistent results require effort
If we all agree that it is important, then why did I spend the time belaboring these points? The answer remains, as it always has, that moisture sensor deployment is not ‘plug and play.’ To have the moisture sensors reduce and/or eliminate wet loads requires a relatively modest level of effort. To achieve repeatable, consistent slump results within one inch (25mm) of specification takes an entirely different level of commitment.
Let’s do a quick check on the arithmetic. A 10 yd3 load (7.6 m3) of concrete with 29,000 lb. (13,180 kg) of two aggregates requires a water adjustment of 8.7 gal (32.8 L) for each 0.25% (SSD) of moisture… if all sensors are calibrated within a cumulative error of 0.25% (SSD) the moisture compensation water will be within 0.87 gal (4.3L) per yd3/ m3.
On the other hand, if the cumulative calibration error of the sensors is within 0.50% (SSD) of the actual moisture, the potential error of the water calculation can be over 17 gal (66 L). It doesn’t take very much error in the calibration of a sensor to have a big impact on the slump.
Managing expectations
Therefore, the expectations of the producer (what is the desired tolerance of the produced slump from design specification) must be understood up front and will govern the moisture sensor deployment process for the sensors(1).
The calibration process, while not difficult, requires time and effort. Although the sensors are pre-calibrated in the factory, it is necessary to calibrate the sensor after installation to correspond to the right material and measuring environment.
For a sensor that makes physical contact (“aka microwave type”) with the material the process involves multiple samples and multiple bakeoffs for best results.
For non-contact sensors (“aka optical infrared”) it is possible to initially calibrate the sensors in a laboratory environment, but final calibration likely requires some physical sampling of material and associated bakeouts.
In either instance be prepared to perform some burn-offs.
Moisture sensor deployment considerations
With all of that said, one final decision is where should the calibration information be configured? Every sensor supplier has a process to calibrate an individual sensor using proprietary software. This software adjusts the sensor behavior itself, so the individual sensor is tuned for its respective material(s) and location(s).
This can be a bit of a burden, as each sensor will likely require its own ‘configuration’ unique to its location/material. Any adjustment to a sensor down the road requires a specific adjustment to its parameters. Whether or not that requires an on-site visit or not is an important consideration when choosing a moisture sensor deployment strategy.
Another method is to limit changes to the sensors from their factory settings to the absolute minimum and use the plant automation system software to calibrate the sensors. This will vastly simplify maintenance and serviceability over the long term.
Finally, consider implementing software that can collect and provide centralized reporting of each sensor’s performance and the water added/dry uploads by the operators. This data can be used to make small adjustments over time to the sensor calibrations without having to rely on burn-offs.
