A Novel Framework for Real-Time Carbon Intensity Measurement in MES-Driven Decarbonized Manufacturing

The Operational Blindspot in Modern Manufacturing
Nov. 14, 2025
5 min read
3694701 © Irochka | Dreamstime.com
Manufacturing floor

Powered by Veronika Furs

The Manufacturing Execution System (MES) has revolutionized the shop floor, providing millisecond-level precision on every metric, except the most critical one, carbon emissions. Despite the global MES market being projected to reach US $29.5B by 2030, manufacturers are still stuck using analog systems such as spreadsheets and manual quarterly aggregates to track carbon emissions. 

This causes delay, ranging between 5 to 60 days for small and large companies, and forces operational decisions that are weeks too late. ESG teams are forced to report sustainability performance using lagged data, while plant managers lacking the granular visibility into when, why, where carbon emissions arise at the line, shift, or machine level, are unable to optimize performance.

Consequently, the gap between operational data and environmental accountability has crystallized into a strategic liability, jeopardizing compliance and preventing real-time Scope 1 and 2 optimizations necessary for decarbonization. 

A novel framework developed by product leader and sustainability strategist, Lesia Yanytska, is addressing this specific operational blindspot. The framework reimagines the MES not only as a production tool but a live carbon tower that can track, alert, and mitigate carbon emissions at the shift, machine, and line level. 

A Novel Innovative Framework for MES-Driven Decarbonization

Yanytska’s patent-pending framework, (USPTO #63/808,207, filed May 2025), is built on a modular architecture and is based on five interconnected layers.

Layer I: The Sensor Level (Foundation)

In this layer, high-resolution IoT sensors capture raw energy consumption data readings from major loads such as HVAC units, gas and electricity ovens, and motors. The readings are timestamped by the sensors, operating on sub-minute intervals and facilitating precise temporal analysis to isolate when emission spikes occur. This granularity reveals which line or process is responsible for emission spikes.
 

Layer II: SCADA/PLC Integration (Routing)

Supervisory Control and Data Acquisition (SCADA) and Programmable Logic Controllers (PLCs) manage equipment automation in the industrial setting. The framework routes the data through this existing infrastructure, leveraging these systems to ensure data integrity and synchronize time-stamps with active production events. 

Layer III: MES Computation (Control)

 
The MES receives the time-stamped sensor data and applies dynamic carbon intensity (CI) factors that transform kilowatt-hours into CO2e emissions computed either as:
 
• Per-unit - kgCO2e produced per product manufactured.
• Per-energy - kgCO2e per megawatt-hour consumed.
 
This dual-mode ensures the framework can adapt across diverse manufacturing contexts without requiring further custom development.
Courtesy Lesia Yanytska
Fig 1 MES CI computation flowchart illustrating how energy input is converted into CI output per SKU/line/shift.

Fig 1 MES CI computation flowchart illustrating how energy input is converted into CI output per SKU/line/shift.

Layer IV: Alert Engine (Intelligence)

An embedded alert engine continuously assesses live CI values against pre-set thresholds. When it detects anomalies, such as exceeding CI during a shift, the engine triggers an alert in a multi-step diagnostic sequence:
 
• Root cause analysis.
• Ticket generation.
• Operator notification. 
 

Layer V: ESG Platform Integration (Enterprise Synchronization)

This layer synchronizes the CI metrics with external ESG platforms such as the SAP Sustainability Control Tower via secure, standards-based APIs.
Courtesy Lesia Yanytska
Fig 2. Proposed real-time CI monitoring architecture showcasing five layers integrating IoT sensors, SCADA/PLCs, MES, and ESG APIs to enable real-time CI tracking, alert logic, and automated reporting

Fig 2. Proposed real-time CI monitoring architecture showcasing five layers integrating IoT sensors, SCADA/PLCs, MES, and ESG APIs to enable real-time CI tracking, alert logic, and automated reporting

Framework Significance – Compliance, Credibility, Competitiveness 

1. Accelerating compliance efforts
 
The real-time synchronization of the MES with industry-standard ESG platforms with secure APIs eliminates the latency and manual labor associated with traditional reporting. The system delivers financial-grade environmental data traceable down to the sub-minute sensor reading, enhancing auditability for compliance with the new CSRD regulations.
 
2. Improved credibility and access to capital
 
In a market where 89% of investors consider ESG reports before making investment decisions, verifiable reductions in Scope 1 and 2 reductions are non-negotiable. By replacing aggregated estimates with primary, real-time CI data, the framework provides the transparency needed to build stakeholder trust. 
 
3. Enhanced competitiveness and operational excellence
 
The framework drives operational excellence by embedding CI as a visible KPI within MES dashboards, empowering plant operators and line managers to act directly on environmental performance. 

Why this Framework is Unique

Yanytska’s framework represents a paradigm shift. It moves carbon monitoring from a passive, retrospective activity, confined to static annual reports or high-level enterprise dashboards, to an active embedded component of the operational workflow. This ensures that decarbonization is alert-driven rather than passive. 
 
The framework also introduces unprecedented granularity, determining Carbon Intensity (CI) at the Stock Keeping Unit (SKU), machine, and shift level. Its uniqueness is also amplified by the utilization of dynamic carbon factors which reflect real-time fluctuations in the energy mix. Finally, vendor-neutrality of the framework means that it can be adopted across different industries using both legacy and modern MES platforms. 
 
Broader Impact on Industry
 
Yanytska’s modular framework has already been validated in real-world simulations. In one FMCG facility it detected a CI spike, and through the embedded alert engine, drove corrective actions that restored normal operations and achieved a 22% CI reduction in only 45 minutes of intervention. This success demonstrates the framework’s power to translate theoretical carbon governance into immediate operational reality. 
 
Across the broader industry, the framework is anticipated to serve as the definitive blueprint for next-generation carbon governance. This ability to act on emissions data in real-time grants manufacturers a competitive edge in operational efficiency and regulatory readiness in reducing Scope 1 and 2 emissions. 
 
Ultimately, Lesia Yanytska’s innovation fulfils the industry 5.0 mandate by seamlessly integrating sustainability into the core of the factory execution. This framework transforms the MES into a resilient carbon control tower that creates long-term value in the low-carbon economy.

About the Author

Veronika Furs

Veronika Furs

Veronika Furs is a Wilmington, Del.–based writer covering engineering innovation, advanced manufacturing and the entrepreneurial forces accelerating the tech sector.

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