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UID:144781-20261007T081000Z@fastenershows.com
DTSTAMP:20260601T160230Z
DTSTART:20261007T081000Z
DTEND:20261007T084000Z
SUMMARY:Intelligent Manufacturing at Scale: AI and the Reinvention of Complex Assembly
DESCRIPTION:Manufacturing is entering a decisive new chapter\, defined not by incremental improvement\, but by a fundamental rewiring of how plants plan\, operate\, and compete.\n \nPerformance pressure is intensifying. OEE losses\, unplanned downtime\, scrap and rework\, and excess working capital continue to erode margins in complex assembly environments. Many manufacturers have invested in digital platforms\, yet fragmented MES\, SCADA\, ERP\, and PLM systems still limit real‑time decision making\, creating an opportunity for AI to deliver innovative\, high‑impact solutions. \nThis session will focus on how AI is reshaping complex assembly operations and creating measurable business impact. Participants will gain insight into how intelligence embedded across the industrial blueprint can deliver competitive advantage\, enhance throughput across OT and IT platforms\, and improve working capital efficiency\, all contributing to stronger margins and operational resilience. Manufacturers that integrate intelligence\, automation\, and human capability into core operations rather than treating them as add‑ons achieve significant performance gains and sustainable competitive advantage.\n \nWhy it matters\n\nGlobal supply chains remain structurally more volatile\, driven by geopolitical shifts and fluctuating demand patterns\nSkilled labor is constrained and harder to upskill at scale as demographic shifts reduce available talent pools \nSustainability expectations now require measurable performance improvements\, not just reporting\nThe technology stack across AI\, automation\, and industrial connectivity has matured to enable speed\, precision\, and resilience simultaneously\nDigital twins are expanding from isolated line simulations to enterprise‑wide decision platforms\nOT cybersecurity is evolving from basic IT hygiene to continuous\, real‑time protection for connected production systems \n\n \nLearning Objectives\n\nDiagnose revenue leakage across complex assembly lines and quantify where AI can create value to improve throughput\, reduce scrap and rework\, and increase asset utilization\nTranslate AI‑enabled automation into measurable gains in OEE with direct impact on margin expansion\nBuild a scalable AI roadmap tied directly to profitability\, working capital efficiency\, sustainability integration\, and operational resilience
LOCATION:Room A
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