Domain: Manufacturing
Question:
In a highly automated, multi-site manufacturing environment, how can integrating Enterprise Resource Planning (ERP) with Operational Technology (OT) be structured to maximize predictive maintenance accuracy and reduce unplanned downtime? Along with the uploaded documents, you can also use the following web resources:
https://www.realvnc.com/en/blog/digital-transformation-in-manufacturing/
https://www.businessinsider.com/artificial-intelligence-robotics-predictive-maintenance-manufacturing-factory-solutions-2025-5
https://www.industryweek.com/technology-and-iiot/emerging-technologies/article/55308070/what-is-edge-ai-and-how-useful-is-it-for-manufacturing
https://www.infosysbpm.com/blogs/manufacturing/cybersecurity-in-the-digital-factory-for-manufacturers.html
https://www.manufacturingtomorrow.com/story/2025/06/from-legacy-to-leading-how-manufacturers-can-bridge-the-integration-gap/25156

Do not generate any output files - just provide the response directly here.

Expected points in a correct answer:
Identify the source report as: Veronesi, L. (2021). Digital Transformation in Manufacturing.
State that the source report identifies segregated IT/OT operating models.
State that the source report identifies integrated IT/OT operating models.
State that cybersecurity has direct business impact.
State that the source report identifies coordinated IT/OT operating models.
State that the unified approach replaces isolated OT data silos.
State that enterprise information management consolidates structured data across the full information lifecycle.
State that the integrated IT/OT model is supported by a standing center of operational excellence.
State that control systems are shared between IT and OT in the integrated model.
State that cloud platforms are identified as a key enabler for scalable integration.
State that execution-level operations are managed through a common platform.
State that the IoT-based layer connects factory technologies with enterprise systems.
State that ERP-OT integration is enabled by an IoT-based layer.
State that enterprise information management consolidates unstructured data across the full information lifecycle.
State that the unified approach replaces isolated ERP data silos.
State that compliance monitoring is a foundational capability.
State that the governed information framework addresses intellectual property exposure risk.
State that the governed information framework addresses data leakage risk.
State that the governed information framework addresses operational loss risk.
State that identity and access management is a foundational capability.
State that information control is a foundational capability.
State that AI-assisted analytics are used to analyze combined OT and ERP data.
State that the center of operational excellence includes permanent staff from business functions.
State that many manufacturers are moving toward an integrated IT/OT model.
State that AI-enabled analytics enable continuous planning.
State that artificial intelligence processes combined OT and ERP information.
State that OT data is generated by production assets.
State that OT data is made available to ERP systems through the IoT layer.
State that OT data is generated by sensors.
State that AI-enabled analytics enable situational awareness.
State that AI-enabled analytics enable root-cause identification.
State that cloud-based architectures maintain security.
State that enterprise information management is supported by advanced analytics.
State that cloud-based architectures support geographically distributed sites.
State that the center of operational excellence includes permanent staff from IT functions.
State that cloud-based architectures allow manufacturers to analyze process-generated information.
State that cloud-based architectures allow manufacturers to share process-generated information.
State that cloud-based architectures allow manufacturers to capture process-generated information.
State that enterprise information management is supported by artificial intelligence.
State that enterprise information management is supported by cloud platforms.
State that cloud-based architectures maintain governance.
State that machine learning processes combined OT and ERP information.
State that OT data is made available to other enterprise platforms through the IoT layer.
State that OT data is generated by automated equipment.
State that in a highly automated, multi-site manufacturing environment, integrating Enterprise Resource Planning (ERP) with Operational Technology (OT) must be structured around a unified, information-centric architecture.
State that manufacturers must implement enterprise information management (IM) to support predictive maintenance at scale.
State that designing ERP-OT integration for predictive maintenance requires prioritizing enterprise information management.
State that cybersecurity must be embedded into information architectures.
State that cybersecurity must not be added later.
State that predictive maintenance accuracy depends on how information is exchanged across factory and enterprise systems.
State that predictive maintenance accuracy depends on how information is governed across factory and enterprise systems.
State that predictive maintenance accuracy depends on how information is captured across factory and enterprise systems.
State that predictive maintenance accuracy depends on how information is analyzed across factory and enterprise systems.
State that mixing advanced analytics applied to enterprise business data with OT data is central to delivering more powerful business applications.
State that the integration structure allows maintenance-relevant operational data to be analyzed together with enterprise information.
State that ERP-OT integration represents a structural change in how manufacturing organizations manage asset health.
State that ERP-OT integration represents a structural change in how manufacturing organizations estimate asset health.
State that the unified, information-centric architecture enables coordinated decision-making across sites.
State that cloud scalability supports predictive maintenance across multiple plants.
State that the single information backbone supports consistent analytics across multiple production sites.
State that the integration structure dismantles traditional IT/OT boundaries.
State that the single information backbone supports consistent decision-making across multiple production sites.
State that reduced unplanned downtime depends on how information is captured, governed, exchanged, and analyzed across factory and enterprise systems.
State that predictive maintenance accuracy improves when high-velocity operational data is analyzed together with enterprise information.
State that organizational integration reduces unplanned downtime.
State that organizational integration enables consistent predictive maintenance analytics.
State that the model anchors central oversight without sacrificing local agility.
State that embedding security and governance enables actionable predictive maintenance insights.
State that harmonizing operating data across different automation maturity levels enables consistent predictive maintenance.
State that integrating ERP and OT within a governed information framework reduces unplanned downtime.
State that predictive maintenance accuracy improves when high-volume operational data is analyzed together with enterprise information.
State that the unified, information-centric architecture enables advanced analytics across sites.
State that this integration forms the basis for the factory of the future.
State that AI-assisted analytics detect deviations invisible to human operators.
State that adopting coordinated integration models enables proactive asset management at scale.
State that embedding security and governance enables reliable predictive maintenance.
State that the integration structure supports real-time decision environments.
State that the unified, information-centric architecture enables continuous visibility across sites.
State that AI-enabled analytics replace isolated maintenance actions.
State that AI-enabled analytics replace reactive maintenance actions.
State that unplanned downtime is reduced by avoiding site-specific approaches.
State that unplanned downtime is reduced by avoiding fragmented approaches.
State that the information-centric approach preserves long-term architectural flexibility.
State that cloud scalability aligns with unified information strategies extending beyond individual factories.
State that the information-centric approach preserves regulatory compliance.
State that the information-centric approach preserves operational resilience across the enterprise.
State that ERP-OT integration exceeds a technology project, when done correctly.
State that scalable integration occurs across factories.
State that scalable integration occurs across ecosystems.
State that information must be treated as the central asset of digital transformation.
State that the unified approach creates a single information backbone.
State that secure plant-floor connectivity is a foundational capability.