34 | Focus on Resins: Hexion
THE NEXT ERA RESINS:
The next era of resin innovation is adaptive chemistry informed by real-time mill data, writes Michael Lefenfeld, President and CEO, Hexion
E
lement has remained largely unchanged: the resin systems that hold every board
together. For decades, resin chemistry has been
delivered as a fixed formulation, optimized in controlled lab settings and expected to perform consistently in production environments that rarely resemble those same lab assumptions. As wood mills face rising pressure on throughput, quality, and cost, this disconnect between static chemistry and dynamic operations has become a structural constraint. The next era of innovation will not come from incremental refinements to existing systems. It will come from resin that adapts in real time to the process conditions that mills actually face. The reality inside a mill, even with the most sophisticated processes, is inherently dynamic due to environmental factors. Moisture content can shift each day depending on the weather. Temperature profiles move with the season, production pace, and equipment condition. Wood species, fines levels, and fiber distribution influence how a resin absorbs
and cures. Equipment behavior, like the press, evolves throughout the day as operators adjust to maintain targets. When chemistry remains fixed but the environment does not, mills are forced to compensate through operational safeguards. They may increase resin usage, slow press speeds earlier than performance requires, they widen quality margins to avoid risk. These decisions protect product quality, but they also raise material cost, reduce productivity, and increase energy consumption. The industry has become highly skilled at managing variability. The opportunity now is to reduce the need for that overcorrection in the first place. This is why the next phase of resin
innovation is not simply a matter of improving resin formulations. It is the shift toward adaptive resin systems informed by real-time wood and mill data, environmental conditions, and AI-driven modeling. The question for the industry is straightforward. Can chemistry become responsive to live operating conditions rather than requiring mills to adjust around assumptions built into fixed formulations?
This shift represents a fundamental rethinking of how resin contributes to wood panel performance, efficiency, and quality.
MACHINE LEARNING MEETS RESIN: FROM REACTIVE CONTROL TO PREDICTIVE PERFORMANCE Real-time data becomes truly valuable when paired with machine learning instead of being stored in a report stuffed into a binder. For the first time, mills can model how resin will behave under actual conditions rather than relying exclusively on historical averages or post-production testing. Across early deployments, predictive accuracy is already within roughly ten percent of measured performance. This capability changes how resin programs operate. Instead of identifying drift only after it appears in quality results, models can signal when performance is likely to move off target. Each batch adds new information. Each run sharpens the predictive model. Each prediction gives operators an earlier and clearer view into what the chemistry is about to do. Machine learning does not replace
operator or resin expertise. It enhances and expands it. It provides real-time data that allows teams to protect quality proactively rather than widening operating margins as insurance. For mills, the impact is tangible and consistent: fewer excursions, tighter internal bond consistency, reduced waste, and a meaningful decrease in the hidden costs created by variability.
Above: Hexion CEO Michael Lefenfeld WBPI | December 2025/January 2026 |
www.wbpionline.com
THE DATA BACKBONE: HOW SMARTECH ENABLES PREDICTIVE AND ADAPTIVE CHEMISTRY Predictive control requires continuous, high-resolution insight into mill operations. Traditional sampling and lab testing provide important information, but only at specific points in time. This is the gap that Hexion’s Smartech AI software platform, coupled with our internal AI-enabled smart resin production, is designed to address. Systems such as SmartQuality, SmartPress, and SmartStrander provide the real-time data foundation that enables adaptive chemistry. AI-enabled decision-support
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