Title: AI Agents for Manufacturing for Maximized Efficiency and Profitability

Authors: Avner Ben Bassat

DOI:

Abstract: The shift from manual planning methods to the era of AI Agents marks a major turning point in composite manufacturing. For years, planning and coordination depended on people stitching information together, often through spreadsheets, experience-based decisions, and constant backand-forth communication. Now, manufacturers are moving beyond those fragmented, errorprone processes toward systems that can reason across thousands of variables, anticipate disruptions, and continuously help make better decisions at every stage of production. Today’s AI agents are built to collaborate, adapt in real time, and continuously improve outcomes, handling levels of complexity that are difficult to manage manually. By combining large language models (LLMs), reinforcement learning, and advanced reasoning, these systems coordinate manufacturing operations with a level of automation, accuracy and consistency that was previously out of reach. In this paper, I discuss how manufacturing technology has evolved from rigid rule-based methods and systems into modern agent-based AI systems that can actively drive goals and KPIs, adapt to changes as they occur, and coordinate work across planning, production, and quality teams. Drawing on composite manufacturing examples, we show how AI agents enable smarter material selection, proactive tool maintenance, more resilient production planning, and continuous quality control, while maintaining full digital thread traceability. In practice, these capabilities have delivered measurable results, including 10-20% improvements in material utilization, a 15% reduction in unplanned downtime, and significant cost savings through predictive maintenance and smarter resource allocation.

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Conference: SAMPE 2026

Publication Date: 2026/04/27

SKU: 100

Pages: 15

Price: $30.00