Domain: Manufacturing
Question:
How can manufacturers integrate ERP and OT data analytics for predictive maintenance while keeping systems secure and scalable? 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 Digital Transformation in Manufacturing (2021) by Veronesi.
State that manufacturers can integrate ERP and OT analytics by treating information as the core business asset rather than as a by-product of systems.
State that predictive maintenance is enabled when enterprise and operational information flows are unified.
State that predictive maintenance is enabled when enterprise and operational information flows are governed.
State that predictive maintenance is enabled when enterprise and operational information flows are analyzed across the full manufacturing environment.
State that the IoT layer connects factory technologies with 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 transition from OT to IT is enabled by an IoT layer.
State that enterprise information management (IM) consolidates information across its lifecycle.
State that enterprise information management eliminates isolated data silos.
State that artificial intelligence acts as the analytical "brain."
State that maintenance-relevant operational data can be analyzed alongside enterprise data.
State that OT data is made available to enterprise systems such as ERP.
State that enterprise information management functions as an "information highway."
State that machine learning acts as the analytical "brain."
State that an integrated model includes a standing center of operational excellence.
State that scalable analytics require movement toward an integrated IT/OT model.
State that predictive analytics require movement toward an integrated IT/OT model.
State that the document identifies three IT/OT integration states.
State that the integration framework is supported by artificial intelligence.
State that the integration framework is supported by advanced analytics.
State that cloud platforms enable scalable integration across factories.
State that cloud platforms enable scalable integration across ecosystems.
State that cloud architectures allow information sharing across suppliers.
State that cloud architectures allow information capture across plants.
State that cloud architectures allow information sharing across partners.
State that the center of operational excellence includes permanent staff from business functions.
State that the center of operational excellence includes permanent staff from IT functions.
State that OT data is generated by production equipment.
State that OT data is generated by sensors.
State that OT data is generated by machines.
State that security has direct business impact.
State that cybersecurity must be embedded within the information architecture.
State that compliance monitoring must be embedded within the information architecture.
State that identity and access management must be embedded within the information architecture.
State that information control must be embedded within the information architecture.
State that security controls must not be added after integration.
State that information must be captured across unstructured sources.
State that information must be captured across structured sources.
State that information must be secured across the extended enterprise.
State that information must be enhanced across the extended enterprise.
State that information must be exchanged across the extended enterprise.
State that information must be governed across the extended enterprise.
State that ERP-OT integration for predictive maintenance requires prioritizing enterprise information management.
State that predictive maintenance emerges when high-velocity information from production processes is analyzed together with enterprise information.
State that predictive maintenance emerges when high-volume information from production processes is analyzed together with enterprise information.
State that integrated data can create more accurate future maintenance algorithms.
State that cloud architectures maintain secure access.
State that centralized governance addresses intellectual property exposure risk.
State that cloud architectures maintain governance controls.
State that centralized governance addresses operational loss risk.
State that centralized governance addresses data leakage risk.
State that cloud scalability supports predictive maintenance across geographically distributed operations.
State that this integration supports real-time decision-making environments.
State that embedding security into architecture enables regulatory compliance.
State that harmonizing operating data enables consistent asset management across automation maturity levels.
State that coordinated integration models improve scalability.
State that a modular integration layer allows manufacturers to scale predictive maintenance in many plants.
State that the information-centric approach enables actionable insights.
State that AI enables situational awareness.
State that AI enables root-cause identification.
State that AI enables continuous planning.
State that combining data flows enables preventive maintenance systems.
State that preventive maintenance systems improve asset reliability.
State that the information-centric approach enables reliable insights.
State that organizational integration supports consistent governance across multiple plants.
State that organizational integration supports consistent analytics across multiple plants.
State that organizational integration supports scalability beyond plant-specific solutions.
State that centralized information governance supports predictive maintenance.