MES as the Enabler of People–Process–Technology Simulation
The concept of the digital twin has taken manufacturing by storm. Most commonly, it is understood as a virtual replica of a physical asset—a machine, a line, or even an entire plant. These models simulate mechanical performance, maintenance needs, and throughput under various conditions. But this view, while powerful, is still limited.
The real opportunity lies in going further: building a digital twin not just of assets, but of the entire manufacturing organization—including machines, people, processes, and rules. This broader view creates what we might call a digital twin of operations. And to build such a twin, there’s one indispensable foundation: a well-implemented Manufacturing Execution System (MES).
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Moving Beyond the Asset-Centric Twin
Most digital twin discussions begin with physical assets. These twins can predict wear, simulate vibration under stress, or test alternate speeds for higher output. While valuable, they focus only on the mechanical dimension of performance.
However, manufacturing outcomes are never the result of assets alone. They are the result of interactions between machines, people, materials, procedures, and decisions. A new machine doesn’t increase productivity unless operators are trained, procedures are adapted, and upstream processes are synchronized.
That’s why building a true operational digital twin—one that reflects reality and drives strategy—requires modeling not only assets, but also:
- Human roles and responsibilities
- Workflows and production rules
- Event sequences and process deviations
- Decision logic, approvals, and escalations
This is not just a digital twin of the plant—it is a digital twin of how the organization works.
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MES: Capturing the Fabric of Operations
MES sits at the heart of the production environment, connecting ERP systems with the shop floor, enforcing execution, and capturing events in real time. It tracks:
- Which operator performed which action
- What materials were consumed, and when
- What deviations or exceptions occurred
- How decisions were made and processes adapted
This means MES doesn’t just know what happened. It knows who did it, how they did it, and under what conditions. It captures context—sequential, temporal, and procedural. And it structures this information in a way that can be simulated, repeated, and analyzed.
This context is what makes MES the essential foundation for building a digital twin of the organization. It reflects not just technical flow, but organizational behavior.
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Simulating People, Roles, and Decisions
Let’s take a practical example: a digital twin of a packaging line.
A traditional twin might simulate speed, downtime, and material flow. An MES-powered twin, however, would also simulate:
- How performance changes across shifts with different teams
- The impact of a procedural change introduced during a continuous improvement initiative
- The delay introduced by manual quality inspections
- The effect of approval workflows when an anomaly is detected
You’re not just simulating machines. You’re simulating decisions, interventions, and procedural behavior—the true levers of performance.
This enables a far deeper form of continuous improvement. Instead of only tweaking machines, organizations can experiment with role redesign, procedural updates, or new escalation paths—virtually—before deploying them physically.
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Enabling the Virtual Enterprise
As manufacturers become more complex and distributed, the value of a comprehensive digital twin grows. With MES feeding data into a centralized model, manufacturers can create:
- Cross-site operational benchmarks
- Replicable best practices for roles and workflows
- Scenario planning at the organizational level (e.g., “How would productivity shift if we moved these tasks from Line A to Line B?”)
This lays the foundation for what we might call the virtual manufacturing enterprise—an environment where operational leaders and system integrators can test, validate, and scale improvements before ever touching physical assets.
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Industry 5.0: A New Context for the Organizational Twin
Industry 5.0 emphasizes human-centricity, resilience, and sustainability. All of these require a broader lens than machine performance.
- Human-centricity means understanding how roles are executed, how decisions are made, and how information flows between people and systems.
- Resilience means being able to simulate how the organization adapts—not just the machines—when disruptions occur.
- Sustainability means simulating procedural changes that reduce waste or improve resource allocation.
All of this depends on having a digital twin that accurately models the organizational dynamics—something only possible with MES data at its core.
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