TL;DR Traditional route-based maintenance is becoming harder to sustain due to workforce shortages. Predictive maintenance requires actionable workflows, not just more data. Machinery health software helps turn condition data into operational decisions. Industrial AI...
TL;DR Operational excellence now requires continuous optimization, not just production output. Edge computing brings analytics and AI closer to the process. Local AI supports faster decision-making and safer operations. Industrial PCs provide the compute power needed...
TL;DR Industrial organizations have more data than ever, but much of it remains siloed. AI requires contextualized, accessible data to deliver meaningful value. Edge architectures provide low-latency access to high-fidelity operational data. Local LLMs improve...
TL;DR Digital twins are evolving beyond operator training. Modern simulation platforms support engineering, testing, and grid integration. Renewable energy projects benefit from improved system-level validation. Hybrid-fidelity modeling helps reduce simulation cost...
TL;DR High OEE does not guarantee optimal operational performance. Bottlenecks often originate outside of equipment effectiveness. Real-time scheduling provides broader visibility into the value stream. Simulation helps identify the root causes behind performance...
TL;DR Many life sciences manufacturers still rely on spreadsheet-based scheduling. Manual scheduling is prone to errors, delays, and limited visibility. DeltaV Real Time scheduling software dynamically adapts to plant conditions. Integrated scheduling improves...
TL;DR Many OT teams are overwhelmed by unstructured data. Data silos limit visibility and prevent actionable insights. Modern edge infrastructure improves data access and context. Edge controllers enable reliable connectivity in remote environments. Low-latency data...
TL;DR Sustainability initiatives require efficient use of limited resources. Automation enables measurable improvements in energy use and emissions. Monitoring WAGES systems is key to identifying waste. Modern control and reliability tools reduce inefficiencies and...
TL;DR Industrial AI requires compute closer to the process. Commercial servers are not designed for real-time OT needs. Deterministic performance is critical for control systems. Thermal constraints can impact edge performance. Modern edge controllers combine control...
Why this matters now As manufacturers push toward higher levels of operational excellence, many have adopted AI and machine learning technologies to close the gap between available resources and rising performance demands. These technologies have delivered step-change...
Why this matters now As industry faces an ever-increasing number of new challenges—workforce reductions, supply chain shortages, increased global competition, and more—operational technology (OT) teams are continually looking for ways to optimize their operations....
Why this matters now The AI revolution is here, and it comes with a very real and growing demand for power. As AI capabilities become embedded into everyday tools and industrial systems alike, the energy required to train and operate these models has grown...
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Emerson Exchange 365
This blog features expert perspectives from Emerson's automation professionals on industry trends, technologies, and best practices. The information shared here is intended to inform and educate our global community of users and partners.