Thouheed Abdul Gaffoor
CEO & Co-Founder, Basetwo AI
Thouheed Abdul Gaffoor is the Co-Founder and CEO of Basetwo AI, a company that deploys digital twins to optimize scale up and manufacturing in the chemicals industry. Thouheed previously served as the Head of AI at Autodesk, and has spent over a decade leading global deployments of AI solutions across multiple industries, working with Fortune 500 manufacturers to improve process efficiency, quality, and sustainability. With a background in engineering from the University of Waterloo, he specializes in applying physics-informed machine learning to solve complex industrial challenges.
Predictive Digital Twins for Optimized Quality Control in Polymers & Adhesive Manufacturing
High Performance Polymers and adhesives are a critical segment of the specialty chemicals industry, serving applications in packaging, hygiene, automotive, electronics, and construction. Polymerization processes are highly sensitive to variations in raw materials, reaction kinetics, mixing, heat transfer, and operating conditions, making consistent product quality difficult to achieve using conventional monitoring approaches alone. Recent advances in artificial intelligence (AI) are enabling a new generation of predictive quality control systems that continuously estimate critical quality attributes and optimize process performance in real time. By combining first-principles process knowledge with machine learning, hybrid AI models can predict key properties such as molecular weight distribution, conversion, viscosity, melt flow index, residual monomer concentration, particle size, and polymer architecture before laboratory measurements become available. These models leverage real-time process data-including temperatures, pressures, flow rates, reactor conditions, and online sensor measurements-to provide early warning of quality deviations, recommend corrective actions, and support closed-loop process optimization. The result is improved product consistency, reduced off-spec production, shorter grade transitions, lower energy consumption, and accelerated scale-up and technology transfer. This presentation explores the application of AI-driven quality control across batch and continuous polymerization processes, highlighting how hybrid digital twins and soft sensors are transforming polymer manufacturing from reactive quality assurance to proactive, predictive process control.
Co-author:
Emma McGlade
Breakout Session XIII – Data-Driven Innovation in Adhesives – 18 September 2026 – 11:30 – 12:00 – Room Fleming – F3