Across the manufacturing sector, organizations increasingly struggle with fragmented systems and isolated data. Information is spread across ERP, MES, SCADA, historians, and custom applications, each using different naming conventions. This makes data hard to find, difficult to trust, and expensive to reuse.
To address these challenges, manufacturers are increasingly adopting a Unified Namespace (UNS) - a structured approach to organizing and sharing industrial data in real time.
What is a Unified Namespace (UNS)?
A Unified Namespace (UNS) is a centralized, logical data structure that defines how industrial data is named, organized, and accessed across an enterprise.
Instead of keeping data locked inside individual systems, the UNS creates a single reference layer where data from machines, production lines, and business systems becomes available in real time.
In practical manufacturing environments, UNS integrates data from:
- MES, ERP, and quality systems
- SCADA, PLCs, and edge devices
- Maintenance and asset management platforms
This approach is widely used in industrial digital transformation projects, including those delivered by TT PSC for global manufacturers.
Why Manufacturers Implement a Unified Namespace
Based on real-world implementations, including TT PSC manufacturing case studies, the most common reasons for adopting a Unified Namespace are:
- Real-time access to operational data
- Standardized data structures across plants and systems
- A single source of truth for production and compliance data
- Improved data quality and reduced manual effort
- A scalable foundation for analytics, AI, and smart factory initiatives
These benefits are consistently observed across industries such as food & beverage, automotive, and energy.
1. Smarter Recipe Management in Food & Beverage
(Transition Technologies PSC – Case Study)
Client: Confidential – Global food & beverage producer (Europe)Integrator: Transition Technologies PSC (TT PSC)
ChallengeRecipe management relied on outdated tools and manual data transfers. Global formulas were copied between plants, causing errors, delays, and high compliance effort. Reporting was slow and audit preparation required significant manual work.
SolutionTT PSC implemented a modern recipe management environment built on a Unified Namespace architecture. Recipes, production parameters, and compliance data were organized in standardized structures and synchronized automatically across sites.
The UNS enabled
- Global recipe governance
- Local adaptation by R&D teams
- Real-time visibility for operators
- Automated compliance reporting
Read the full TT PSC case study
Impact
- 70% reduction in manual recipe handling
- 50% faster rollout of new and updated recipes
- Over 90% reduction in operator errors
- Audit-ready, automated reporting
2. Real-Time Data Integration in Automotive Manufacturing
Client: Confidential – Tier 1 automotive manufacturer (North America)Integrator: Opto 22 & Inductive Automation
ChallengeThe manufacturer operated multiple production lines and plants using heterogeneous automation systems and proprietary data structures. Operational data from machines, sensors, and control systems was siloed, limiting real-time visibility and making enterprise-level reporting slow and unreliable. Engineering teams struggled to access consistent data for performance monitoring and decision-making.
SolutionA Unified Namespace architecture was implemented to standardize and expose machine and sensor data in real time. Using MQTT-based communication and a structured namespace model, data from shop-floor systems was made available to MES, analytics, and reporting tools without tight point-to-point integrations.
The UNS enabled
- Standardized naming and data models across plants
- Real-time access to machine and process data
- Decoupling of data producers and consumers
- Faster integration of new applications and dashboards
Impact
- Near real-time production reporting across plants
- Reduced integration complexity and maintenance effort
- Faster response to production issues
- Improved scalability of digital manufacturing initiatives
3. Boosting Throughput Across Automotive Supply Chains
(Unified Namespace with MQTT – External Case Study)
Client: Confidential – Leading automotive supplier (Europe)Integrator: i-flow
ChallengeThe organization relied on multiple enterprise and operational systems (ERP, MES, SCADA, CMMS) that exchanged data in batches or via custom integrations. This resulted in delayed information flow, inconsistent KPIs, and limited ability to react quickly to disruptions across the supply chain.
SolutionA Unified Namespace was introduced as a real-time data backbone, using MQTT to connect operational and business systems. Production, logistics, and maintenance data were structured in a common namespace, enabling consistent data consumption by multiple applications simultaneously.
The UNS enabled
- Near real-time synchronization between ERP and shop-floor systems
- Standardized production and logistics data models
- Improved transparency across the supply chain
- Faster rollout of new analytics and monitoring use cases
Impact
- Increased production throughput
- Faster identification of bottlenecks
- Reduced delays caused by data latency
- Improved coordination between operations and planning teams
4. Unified Namespace for OEE Optimization
(OEE Standardization with UNS – External Case Study)
Client: Confidential – Tier 1 automotive supplier (Europe)Integrator: HiveMQ
ChallengeOEE (Overall Equipment Effectiveness) metrics were calculated differently across plants and production lines. Data was collected from various systems using inconsistent definitions, making benchmarking unreliable and limiting management’s ability to compare performance across sites.
SolutionA Unified Namespace was implemented to standardize equipment, production states, and performance metrics across all plants. OEE-related data was published in real time to the UNS, ensuring that all systems consumed the same, consistently defined information.
The UNS enabled
- A unified OEE data model across equipment and plants
- Real-time availability of performance metrics
- Consistent KPI definitions for management and operations
- Easier integration with analytics and reporting platforms
Impact
- Comparable OEE metrics across sites
- Improved transparency of equipment performance
- Faster identification of losses and inefficiencies
- Stronger data foundation for continuous improvement programs
5. Autonomous Business Planning in Industrial Operations
(Unified Namespace for Predictive and Autonomous Operations – External Case Study)
Client: Confidential – Oil & Gas company (Middle East)Integrator: HiveMQ
ChallengeOperational data from production assets, maintenance systems, and business applications was fragmented and not available in real time. This limited the organization’s ability to perform predictive maintenance, optimize planning, and automate business decisions.
SolutionA Unified Namespace was deployed to consolidate operational, maintenance, and business data into a single, real-time reference layer. By decoupling data sources from consumers, advanced analytics and AI-driven applications could access consistent, up-to-date information.
The UNS enabled
- Real-time integration of operational and business data
- Predictive maintenance based on live asset information
- Automated decision-making and planning workflows
- Scalable support for advanced analytics and AI use cases
Impact
- Reduced unplanned downtime
- Improved maintenance planning accuracy
- Faster, data-driven business decisions
- Progress toward autonomous industrial operations
