Wood Moisture Applications
Dictate the Quality & Efficiency of the Process
Moisture Level Sensing Applications For Wood Products
Managing the moisture content in wood products is among the most significant issues in production of the forest and wood industry. An unwanted amount of moisture can cause large impacts on the final product quality and also interfere with proper production. MoistTech’s NIR (near-infrared) moisture sensor allows wood manufacturers to easily adjust moisture levels on real time information. Proper moisture measurement and management can create lower raw material and fuel costs, provide higher returns, as well as produce much more consistent product.
With numerous years of knowledge and experience in the wood and forest processing industry, MoistTech maintains an innovative wood moisture sensor that out performs all competition. The sensors are utilized for non-contact measurements of moisture in forest products such as fiber, sawdust, hog fuel, wood flakes, and wood particles.
MoistTech boasts thousands of installations worldwide, including a variety of forest products, offering both online and laboratory NIR moisture sensors for spot tests in your lines or quality control labs.
The MoistTech IR-3000 moisture sensor has been used extensively within the wood products industry and is ideal for process control of dryers, blenders and incoming raw material providing real-time moisture measurement. Installation is quick and simple and only needs the wood moisture sensor to be mounted a few inches above the product. MoistTech’s product database allows us to pre-calibrate the wood moisture sensor. With known product moisture samples each instrument can be calibrated within a few minutes prior to shipment. Field installation then becomes even simpler.
The IR-3000 stores calibrations that can be transferred to other instruments on similar process applications. Each wood moisture sensor is identical, which then allows calibration settings to be used on all instruments on the same application ranges. Standard power requirements and all outputs are incorporated. The sensor provides extensive data through Ethernet connection or if required has several 4-20 ma outputs together ever other common output. Operator interface and digital displays can also be provided. For additional information or to discuss your application, please contact MoistTech.
Benefits of Wood Moisture Analysis
- Instant real-time feedback with thousands of measurements per second
- Reduced energy usage and downtime
- Reduction in fire and explosion risk
- Plant production efficiency monitoring
- Dryer control
- Blending monitoring for control of moisture & resin
- Increased productivity allows operators to make critical process adjustments
- Low cost – INSTANT ROI!
- Highest performance operation
- Pre-calibrated from the factory, no recalibration required
- Little to no maintenance
- Withstand harsh environments – not sensitive to to heart or humidity
- Non-contact, non-drfit optical scan with +/- 0.05% accuracy
Our products can also be used with the following types of products and industries:
Wood Product Veneer
Moisture content of wood affects many wood properties such as strength, drying, glue curing and bond performance. Moisture measurement is an important part of process control during veneer production in order to keep pace with the flow of materials. With MoistTech’s NIR moisture sensors real-time data is fed directly to the mills distributed control system for process control.
Wood Product Blending
Product that is put to the blender is critical to the plant operation. Correct wood moisture content will allow for precise blending addition that in turn will reduce waste and provide significant cost savings. Many plants report savings alone pay for the cost of moisture / resin control within weeks of installation. At the exit of the blender the process can be refined to confirm the correct resin addition thus preventing press explosions from high moisture in the forming process. Blown boards can be eliminated and precise moisture / resin control will ensure excellent board properties. Trend analysis that is incorporated into the software in each sensor will allow the operator to prevent problems before they cause production interruptions
Raw Material & Hog Fuel
Another important concern of the forest industry is to trying to monitor the quality of raw material going into the mill. Moisture information is needed to determine how much wood a mill is purchasing since much of the pulp wood is purchased on weight. Also, process monitoring is essential due to the variations of quality of the raw wood materials used. An excess of moisture will affect resin coatings causing de-laminating and blown boards. Incoming raw material can be monitored to within 0.5% which allows the dryer personnel to prevent major process changes resulting in interruptions. Dryer in feed can be controlled thus allowing the output to maintain precise moisture levels to within 0.1% accuracy. On hog fuel applications the material can be blended for a more efficient combustion and significant fuel cost.
Wood Product Dryer Measurement
Lumber drying is one of the most expensive and important phases of hardwood processing to help improve lumber quality and lower dryer costs. Incoming wood moisture measurement together with feed rate can prevent overloading the dryer. Mills that use NIR for moisture measurement and control benefit from a reduction in fuel consumption and maximization of energy efficiency by reducing CO2 emissions during drying. Additionally reducing “dusting” that occurs when heat is too high and moisture is too low resulting in product loss. Additionally, measurement of material at the exit ensures that material going to the blender if at the optimum moisture content for resin addition as well as optimizes moisture prior to the palletizer (10-20%). Moisture measurement at the exit of the dryer can save significant amount of fuel while more importantly prevent fires or explosion risk. Trend analysis that is incorporated into each sensor can be used to give operator knowledge of problems before they happen.