Hexion, a 170-year-old chemicals group better known for adhesives and resins than digital experimentation, is trying to recast itself as an AI-enabled manufacturing business, with procurement among the functions being reshaped.
Speaking on SupplyChainBrain, chief procurement officer Gaël De Martelaere said the company has used artificial intelligence across supply chain planning, plant operations, product quality and sourcing, with the aim of improving yields, cutting scrap, l...
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ifting productivity and reducing raw material waste. He described the effort as part of a broader attempt to “reinvent” Hexion, while also stressing that AI still has clear limits.
That message fits with the company’s wider strategy. Hexion has said it is moving away from a commodity-style model towards what it calls a performance and solutions-led approach, supported by advanced analytics, new leadership appointments and a stronger emphasis on digital tools. The firm has also acquired Smartech, an AI-focused manufacturing technology company, in a move intended to deepen its automation capabilities, particularly in wood processing.
In other company material, Hexion has argued that many mills are data-rich but analytically underpowered, meaning they collect information during production but do not always turn it into useful operational guidance. Its response has been to use AI to detect patterns, manage process variation and help operators make faster decisions on the factory floor. The company has also launched SmartQuality, an AI-driven system unveiled at LIGNA 2025, which it says is designed to improve efficiency and sustainability in wood panel manufacturing.
The push is part of a broader industrial trend in which manufacturers are testing whether AI can move beyond pilot projects and into day-to-day operations. At Hexion, the bet is that machine learning can support not only productivity and quality, but also the kind of sourcing and planning decisions procurement teams face when supply chains are volatile.
Even so, De Martelaere’s comments suggest caution alongside ambition. The promise of AI may be substantial, but in a business built on complex processes and physical production, the technology still depends on human judgement, operational discipline and trust.
Source: Noah Wire Services
