Martin Szerment
AuthorPublished on December 13, 2025
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If someone in 2025 still thinks of an MES system as "terminals at workstations and reports from the department," it's about as current as a fax machine in OT-IT integration. The Manufacturing Execution System has ceased being a shop floor application. MES has become the operational layer of truth between the world of automation (OT) and the business world (IT).
MES systems in 2025 are operational platforms that determine whether a company thrives on availability, quality, lead time, and energy efficiency. The MES system has stopped being a cost—it has become a mechanism for steering competitiveness.
MES vs ERP vs SCADA: Where Are the Boundaries?
The key distinction you must understand:
ERP answers the question: what and when should the company produce. MRP planning, purchasing, warehousing, finance—but without execution details.
SCADA answers the question: what's happening at the machine. Monitoring, visualization, alarms—but without business context.
MES system answers the question: how production is being executed here and now—and how to tie it to business. MES tracks orders, WIP, quality, traceability, downtimes with context. The Manufacturing Execution System is the bridge between planning and execution.
The simplest definition:
- SCADA sees signals
- ERP sees documents
- MES system sees production
Why Is an MES System Critical Right Now?
Real-time Is No Longer a Luxury
Downtimes and quality aren't a reporting problem, but a financial one. If the decision to react is delayed by 30-60 minutes, in many industries that's equivalent to "we're not reacting." The MES system must deliver data immediately.
Data in MES Systems Must Have Context
In 2025, the winning company isn't the one with the most data. The winner is the company whose MES system delivers data that is consistent, semantically described, process-linked, and auditable.
Modern MES System Architecture: UNS + Sparkplug B
Classic point-to-point integration in MES systems (PLC → SCADA → SQL → reports) leads to chaos: costs grow non-linearly, changing one source breaks three integrations.
Solution: UNS (Unified Namespace)
The MES system becomes a natural consumer and producer of data in one coherent event ecosystem. In practice, UNS for MES systems is built on:
- MQTT broker as transport
- Sparkplug B as data model standard for MES
- Namespace understandable to the MES system
- Versioning and ownership rules
Why Is Sparkplug B Critical for MES Systems?
MQTT by itself is just transport. Sparkplug B adds to MES architecture:
- Consistent data publication model (NBIRTH/DBIRTH, NDATA/DDATA)
- Device state management—the MES system knows whether a device is online
- Data quality—MES receives quality information for each measurement
- Birth certificate—the MES system doesn't need manual configuration
Effect: when the number of machines and signals grows, the difference between "plain MQTT" and "Sparkplug B" in MES architecture becomes dramatic.
MongoDB vs InfluxDB in MES Systems
An MES system manages at least four data classes:
- Production events (downtimes, changeovers, operations)—with full context
- Time-series (temperatures, pressures)—high-frequency
- Production model (orders, routes, recipes)
- Documents (inspection results, checklists, comments)
When MongoDB in MES architecture?
- Dynamic schemas—different machine types in MES
- Complex event documents—the MES system stores downtimes with cause, comment, parameter snapshot
- Event store—the MES system needs documents with indexes
When InfluxDB in MES system?
- Millions of data points daily
- Efficient windowed aggregations for MES analytics
- Compression and time-series retention
Conclusion: "One database for everything" in an MES system ends in mediocrity. Better to consciously separate storage according to data characteristics.
OmniMES: Next-gen MES System in Practice
OmniMES represents practical implementation of the discussed concepts:
- UNS + Sparkplug B from the start—native connector, device auto-discovery, plug-and-play
- MES as event layer with context—not just tags, but production events with full business context
- Hybrid data architecture—MongoDB for context and events, InfluxDB for time-series
- API-first design—RESTful API and GraphQL, webhooks for event-driven integrations
- Modular architecture—start with core modules (dispatching, data collection), gradual expansion to AI, predictive maintenance
Real-world impact of OmniMES MES system:
- 40-60% reduction in MES system deployment time
- 8-15% increase in OEE through real-time visibility
- 50% reduction in MES integration costs
- Time-to-insight below 1 minute
AI in MES Systems: Not "Whether," But "Why"
AI in production makes sense only when the MES system delivers data with context, consistent events, and KPI definitions.
Examples of real AI applications in MES systems:
- Downtime cause classification—MES system + AI learning from operator corrections
- Failure prediction—MES connects maintenance data with process signals
- Energy optimization—MES system monitors consumption in production context
Conclusion: AI without an MES system is a turbocharger on a bicycle. The MES system is the foundation on which AI can operate effectively.
Summary: MES System as Strategic Decision
In 2025, MES systems aren't isolated applications, but platforms integrating all aspects of production operations. The Manufacturing Execution System is the backbone of production data, the bridge between strategy and execution, the foundation of Industry 4.0.
A modern MES system is based on:
- Sparkplug B for device communication
- MongoDB and InfluxDB for efficient data management
- API-first design for seamless integration
- UNS as common data backbone
Factories that invest in modern MES systems today will be Industry 4.0 leaders tomorrow. The MES system in 2025 is no longer optional—it's a necessity.
Read the Full Article
This text is a shortened version of an extensive, technical article on MES system architecture in 2025. The full version includes:
- Detailed ISA-95 analysis and 11 MES system functions
- Reference flow OT → MES → ERP
- Implementation challenges and security best practices
- Code examples and MongoDB data structures
- Trends: Digital Twin integration, Autonomous operations
Read the full article here:
MES in 2025: The Complete Guide
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