Virtualization, digital twins and performance management tools support the shift to autonomous industrial operations.
Virtualization, digital twins and performance management tools support the shift to autonomous industrial operations.
Industrial autonomy requires more than traditional automation. It calls for:
Honeywell's integrated approach helps connect processes, assets, people and insights to support more adaptive, efficient operations.
Experion PKS HIVE allows decoupling control applications, I/O modules and IT workloads from physical platforms. PKS HIVE enables universal software-based control on any hardware.
IO HIVE: field-distributed I/O, flexible assignment
Control HIVE: logical controller clustering
IT HIVE: centralized VM hosting, reduced local IT
Up to 30% capital savings1
A large capital project can realize up to 30% capital savings in automation infrastructure projects with LEAP™ methodology.
Enhanced system longevity
PKS HIVE decouples control applications from hardware platforms, enabling extended lifecycles and migration without rip-and-replace.
80% reduced cost
Honeywell’s virtualization technology reduces IT costs by eliminating the amount of physical IT nodes by as much as 80%2
Experion PKS HIVE decouples IT workloads from local process facilities by using virtualization to host control system virtual machines either onsite or at centralized data centers. This architecture eliminates significant IT infrastructure costs. The platform uses virtualization hardware at both local and central locations, allowing customers flexibility in where they run their VMs while maintaining the same high reliability. By centralizing IT infrastructure, organizations can reduce hardware costs, simplify lifecycle management and enable central operations capabilities.
LEAP™ (Lean Execution of Automation Projects) is an award-winning methodology that separates physical and functional design, enabling parallel workflows and standardized designs. The approach uses Universal I/O Cabinets, virtualization, cloud engineering, and auto-device commissioning to decouple system hardware from application design. Allowing parallel workflows can save significant schedule time and reduce rework.
AI analyzes data from multiple systems to help surface patterns, anticipate potential equipment degradation and recommend corrective maintenance or operational actions. Explainable AI techniques that combine probabilistic and deterministic models with causal reasoning are designed to enable transparent decision-making. Predictive analytics can help flag deviations or anomalies early by aggregating asset and process data, enabling earlier intervention before issues escalate. AI-enabled platforms offer assistive guidance to staff by contextualizing operational information and highlighting potential actions to consider. AI-supported integration converts equipment, process and operational data into actionable insights for continuous monitoring and helps organizations move towards more adaptive and efficient operations.
