
Learning objectives Understand why process manufacturers are shifting from incremental upgrades to artificial intelligence (AI)-led, scalable automation as a response to volatility, legacy systems and skills shortages. Learn how AI-enabled automation, such as predictive maintenance, digital workflows, digital twins and real-time asset health, directly improves uptime, quality, throughput and time to market. Recognize the strategic value of integrated one-stop engineering and digital delivery models in modernizing plants consistently across multiple sites with measurable business outcomes. Automation insights Automation can assist process industries meet demands even as volatility continues. AI-led technologies can help fill skill gaps in process industries. Companies that embrace modernization not just as a technology upgrade but as a complete reinvention of the plant will be at the forefront of the AI-automation revolution. Plant operators worldwide are struggling to cope with a growing mismatch between their factory capabilities and evolving market expectations. As global manufacturing demand volatility continues unabated, there is a corresponding rise in the need for flexible and digitally augmented operations. Legacy control systems, placed on top of aging assets, further intensify the challenge. And consequently, manufacturers are increasingly prioritizing three pillars. Legacy system upgrades Existing equipment, obsolete control technologies and standalone operational technology (OT) networks create blind spots in plant performance. Modernization, therefore, involves migrating aging programmable logic controllers (PLCs) and human-machine interface architectures to contemporary, secure and more scalable platforms leveraging any-to-any technology synergies. This helps create unified data pipelines across PLCs, Supervisory Control and Data Acquisition (SCADA), historian, Manufacturing Execution System (MES), Enterprise…
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