Industry
Manufacturing & Industrial
We help industrial enterprises modernize distributed applications and infrastructure, move suitable workloads to cloud or hybrid platforms, and improve automation, resilience and operational control.
Manufacturers need to modernize technology while factories continue producing.
ERP, MES, PLM, quality systems, industrial equipment, automation and supply-chain platforms have often developed separately over many years. Changing one layer can affect production, traceability, maintenance, engineering and plant availability.
Nubes Consulting helps industrial organizations modernize these environments, connect IT and OT systems and build reliable data and engineering platforms, while keeping production continuity and operational control visible throughout the change.
Connect enterprise technology with production reality
Manufacturing transformation does not stop at ERP, and it does not start with moving machine data into cloud.
Business planning, engineering, production execution and physical control operate at different speeds and have different reliability requirements. A useful architecture respects those boundaries while making information easier to exchange between them.
ISA-95 describes this problem through the relationship between enterprise systems, manufacturing operations management and control systems. Its purpose is specifically to reduce the cost, risk and errors created when these domains need to exchange information.
Connect what needs to exchange information. Keep clear boundaries around what needs to remain operationally independent.
Where manufacturing technology leaders are focusing
Seven areas where architecture, integration and delivery decisions determine whether industrial technology can change safely.
Modernize production execution without forcing every plant through one big-bang change
MES environments often contain years of plant-specific workflows, equipment integrations, custom reports and connections to ERP, quality and automation systems.
The modernization strategy should therefore depend on what already exists.
Manufacturing technology ecosystem
Different manufacturing models need different platforms. Discrete manufacturing, electronics, automotive supply, process manufacturing and highly automated factories do not have identical production or integration requirements.
Nubes Consulting therefore evaluates platforms around the operating model rather than assuming one manufacturing stack fits every plant.
Technology from enterprise planning to the plant edge
Industrial standards and platforms, alongside the engineering technologies that support them.
Create a shared view of production without creating another integration layer
Manufacturers often have the same data represented differently in ERP, MES, historians, maintenance platforms and machine controls.
Before advanced analytics or AI becomes useful, those systems need common context.
ISA-95 and IEC 62264 give manufacturers a technology-neutral model for the interface between enterprise and production systems. OPC UA provides semantic industrial interoperability, while MQTT with Sparkplug can support event-oriented distribution of plant information.
Depending on the environment, this can be implemented through direct integration, an industrial integration layer or a Unified Namespace-style architecture. A Unified Namespace is an architecture pattern, not a requirement — the right design depends on site scale, existing automation, data volume, latency and who needs to consume the data.
Machines describe production. MES gives it operational context. ERP gives it business context. A well-designed data architecture allows those views to meet without making any one platform responsible for everything.
Connect product design, production and service data across the lifecycle
Digital twins create value when they connect a real asset or process to useful engineering and operational information.
They should not become another 3D visualization project with no operational owner. ISO 23247 provides a formal digital-twin framework for manufacturing, including representation, information exchange and a digital-thread model across the lifecycle.
In Europe, industrial data sharing is also moving beyond individual factories. Manufacturing-X is developing cross-industry data ecosystems built around open standards, data sovereignty and shared value-chain information, and Catena-X applies a similar model specifically to the automotive ecosystem.
For relevant clients this creates architectural needs around data ownership, product identity, semantics, access policy, supplier exchange, digital twins, product genealogy and lifecycle information.
The important point is not to join every data space immediately. It is to make internal product and production data structured enough that sharing it later is realistic.
Put processing close to production when production depends on it
A factory is different from a standard enterprise office.
External connectivity may fail. A cloud region may be unavailable. Latency can matter. A machine or production line may need to keep working regardless.
Cloud can support the factory. The factory should not automatically depend on cloud for every critical action.
We help divide workloads between machine and control, plant edge, site infrastructure, central data centers and cloud.
Local and edge: immediate process data, buffering, local analytics, machine vision, bounded inference and degraded-mode operations.
Cloud and central platforms: fleet-wide analytics, long-term history, cross-site reporting, AI training, enterprise integration and central management. The exact split depends on the production process.
Use equipment data to improve the lifecycle of the asset
Industrial assets have two costs: the cost of owning them, and the cost of them not being available when needed.
We help connect equipment telemetry with maintenance, production and business context, so operational teams can move from isolated machine alerts toward asset-level decisions. That can support condition monitoring, maintenance planning, predictive models, failure analysis and lifecycle management.
ISO 55001 provides a management framework for balancing asset performance, risk and expenditure across the asset lifecycle. Energy is another increasingly important data domain, and ISO 50001 uses measured information and continual improvement to help organizations manage energy performance.
This makes industrial data useful for more than OEE: production, maintenance, energy and asset economics can be viewed together.
Use AI where production data is reliable enough to support it
AI can create real value in manufacturing because factories generate large volumes of repeated process and equipment data.
Useful areas can include predictive maintenance, visual quality inspection, anomaly detection, production optimization, energy analysis, engineering assistance and operator support.
But the main constraint is often not the AI model. It is missing context, inconsistent tags, poor historical data, undocumented equipment and weak integration between production systems.
So our approach starts with the industrial data architecture. AI should sit on top of trusted production information, not become a replacement for it. For machine-control or safety-related actions, model output needs a much stronger engineering and validation process than an office productivity use case.
Use AI to support production decisions. Keep deterministic control and safety boundaries explicit.
Design around production, not around the data center
Six principles that shape how we design, build and operate systems across an industrial estate.
Design against the standards that apply to the plant and the product
Manufacturing requirements depend on country, industry, product, production process and whether the organization develops connected machinery or only operates it.
Nubes Consulting uses applicable regulation and recognised industrial standards as architecture and engineering inputs. Formal safety, product conformity, regulatory and certification decisions remain with the client and qualified specialists.
Global and cross-industry
- ISA-95 / IEC 62264 — enterprise-to-manufacturing integration and MOM architecture
- ISA-88 / IEC 61512 — batch-process control where relevant
- ISA/IEC 62443 — cybersecurity for industrial automation and control systems
- OPC UA — semantic and vendor-independent industrial interoperability
- MQTT and Sparkplug — event-oriented industrial messaging and state handling
- ISO 22400 — manufacturing operations KPIs
- ISO 23247 — manufacturing digital-twin architecture
- ISO 55001 — asset management
- ISO 50001 — energy management
- ISO 9001 and ISO 14001 — quality and environmental management where relevant
Functional safety standards such as IEC 61508, IEC 61511, IEC 62061 or ISO 13849 become relevant for specific equipment and industries rather than every technology project.
European Union and EEA
- NIS2 — can apply to medium and large organizations in several manufacturing categories, including medical devices, electronics, machinery, motor vehicles and other transport equipment
- EU Data Act — applies since September 2025 and directly affects connected products including industrial machinery, by creating rights around access and sharing of product-generated data
- Cyber Resilience Act — affects products with digital elements. Reporting obligations started in September 2026, with the main product requirements applying from December 2027
- EU Machinery Regulation — replaces the previous machinery regime and applies from January 2027
- Digital Product Passport and ESPR — being introduced progressively across product groups, with the EU DPP infrastructure operational in 2026
- GDPR and the EU AI Act — according to the data and AI use case
The useful technology response is therefore not a separate compliance application for every rule. It is better product identity, traceability, security evidence and data governance across the industrial lifecycle.
United Kingdom
Typical reference points include UK product and machinery safety rules, UK GDPR where personal data is involved, NCSC cybersecurity guidance and sector-specific requirements.
For OT architecture, the UK participates in international OT-security guidance that emphasizes secure, controlled connectivity and business continuity across cyber-physical environments.
North America
- NIST Cybersecurity Framework 2.0
- NIST SP 800-82 — operational technology security, which specifically recognises that performance, reliability and safety requirements differ from ordinary IT
- CISA industrial and critical-infrastructure guidance
- ISA/IEC 62443
- Product- and industry-specific requirements depending on areas such as automotive, food, pharmaceuticals, electronics or aerospace
Middle East
Saudi Arabia: the National Cybersecurity Authority Operational Technology Cybersecurity Controls (OTCC) establish specific minimum requirements for OT and ICS environments, and complement the national Essential Cybersecurity Controls.
UAE: national information-assurance requirements may apply to designated critical entities, while Dubai also maintains an ICS security standard for relevant government and critical-infrastructure environments.
Product, industrial-zone and sector requirements then depend on the actual operation.
Asia-Pacific
Singapore: the OT Cybersecurity Masterplan 2024 explicitly addresses both critical and non-critical organizations operating industrial control and OT systems, and promotes secure-by-deployment practices throughout the system lifecycle.
Australia: current OT guidance emphasizes assessing connectivity risk, limiting exposure and using controlled, monitored connections between OT, business systems and external services.
Local safety, product and critical-infrastructure rules should then be assessed according to the plant and industry.
Standardize enough to scale. Keep enough local control to run the plant.
Global companies often have ten, fifty or hundreds of production sites. One extreme creates a different architecture in every plant. The other forces every factory into a central template that does not match local equipment and production realities.
Understand the production flow → Map IT, OT and assets → Define common architecture → Identify plant-specific constraints → Pilot one line or site → Run coexistence → Stabilize → Scale through reusable patterns
The first site proves the architecture. Later sites should reuse the integration patterns, security controls, platform services and deployment automation rather than repeat the original project from zero.
Create a global pattern, not a global exception process.
Use Nubes Consulting where enterprise architecture and plant technology need to meet
A manufacturing program can draw on any part of the service portfolio, in the combination the engagement actually needs.
Architecture & Technology Advisory
Manufacturing architecture, MES strategy, IT/OT integration, industrial-data architecture and independent platform assessment.
Legacy Modernization
Modernize long-lived plant applications, databases, custom interfaces and enterprise-to-production integration.
Cloud Platforms & Operations
Design central, plant, edge and cloud infrastructure supporting industrial workloads.
DevOps & SRE
Introduce software delivery, automation, platform engineering and observability into the parts of the manufacturing estate where those practices fit.
Cloud Migration
Assess and migrate manufacturing-supporting workloads where hosting change is part of the wider transformation.
Engineering Teams & Managed Delivery
Senior architects, platform engineers, DevOps and SRE specialists and delivery teams for defined manufacturing technology workstreams.
Manufacturing experience behind Nubes Consulting
The experience behind Nubes Consulting includes work for Jabil, a large international electronics manufacturer, on a program assessing migration of data-center infrastructure supporting important technology processes in manufacturing plants.
The work included auditing the DevOps and infrastructure environment, reviewing application architecture and source-code quality, analysing performance and evaluating the first cloud-migration proof of concept. The assessment led to recommendations and changes to the migration strategy before wider execution.
Frequently Asked Questions
Do you implement MES platforms?
We can provide architecture, integration, infrastructure, migration and engineering delivery around MES and MOM programs.
Where deep product configuration or production-process expertise is required, we can work together with the platform vendor or an experienced manufacturing specialist.
Do you recommend one MES vendor?
No. The right platform depends on manufacturing type, ERP and PLM environment, number of plants, existing automation, quality requirements and operating model.
We prefer to evaluate platforms against the target architecture rather than start from a reseller relationship.
Do plants need to move their systems to cloud?
No. Some workloads benefit from central cloud services. Others need plant-local or edge execution because of latency, availability, data volume or operational requirements.
Hybrid architecture is normal in manufacturing.
Can old machinery be connected to modern data platforms?
Often, yes. Existing equipment can sometimes be integrated through OPC servers, industrial gateways, protocol conversion, historians or edge platforms.
The appropriate method depends on the equipment, available interfaces and whether connectivity can be introduced safely.
Do you work with SCADA and PLC environments?
We can design the surrounding architecture, connectivity, infrastructure, security boundaries and integration with enterprise systems.
Specialist control logic, PLC programming and functional-safety engineering should remain with qualified automation engineers where required.
What is the role of OPC UA and MQTT?
They solve different parts of the industrial interoperability problem. OPC UA provides industrial information models and secure structured exchange.
MQTT is a lightweight publish and subscribe protocol, while Sparkplug adds conventions useful for industrial state and telemetry. They can be complementary rather than competing choices.
Can AI be used directly in the production process?
Yes, but the level of autonomy should match the risk. AI can be useful for quality inspection, predictive maintenance, anomaly detection, optimization and decision support.
Production or safety-critical control needs stronger deterministic boundaries, validation and human or control-system authority.
Can Nubes Consulting work with our automation and equipment vendors?
Yes. Industrial transformations normally involve ERP, MES, PLM, automation, machine, cloud, security and internal engineering teams.
Nubes Consulting can provide architecture and technical-delivery leadership across those boundaries, while specialist vendors retain ownership of their equipment and process domains.
Modernize industrial technology without disconnecting it from production
Nubes Consulting Digital helps manufacturers modernize production systems, industrial data, plant infrastructure and engineering platforms through practical architecture and controlled delivery. We connect enterprise IT with the realities of operational technology, keeping production continuity, interoperability, security and long-term maintainability visible throughout the change.
Turn your Technology Challenge into a clear Delivery Plan
Nubes Consulting Digital helps design, modernize and operate complex technology environments. From Cloud and Architecture to DevOps, SRE and Engineering Delivery, we focus on practical decisions, reliable execution and measurable business outcomes.
