ValueTwin connects the physical and operational structure of your business with the data generated by it.
The result is a visual analytical environment where teams can explore the operation, investigate changes and understand relationships.
Sophisticated visual showing a continuous journey from a physical manufacturing plant to a visual operational model and then to operational insight. Physical operation left, connected data center, contextual operational analysis right. 16:9.
We first understand how the operation is structured. That can include:
The objective is not to create a digital representation for its own sake. The objective is to create a model that reflects the way the operation actually works.
Visual transformation where a real manufacturing plant gradually becomes a structured operational model. Machines, processes, locations, material flows and states becoming connected model elements. 16:9.
Your existing operational data is connected to the relevant parts of the model. Data can come from systems such as:
The data does not remain isolated. It gains operational context.
Enterprise industrial data integration visual. Existing operational systems feeding into corresponding machines, processes and events within a visual manufacturing model. 16:9.
Users can navigate through the operation rather than through disconnected reports.
Start with the plant. Move into a line. Investigate an asset.
Examine an event. Follow the relationship. Open the underlying data.
The context stays with you as you move deeper.
Product-style visualization of a user navigating an interactive manufacturing operation from plant overview to production line to individual machine. Visual zoom/navigation with contextual KPIs. 16:9.
Operational performance changes over time. ValueTwin helps teams examine the sequence of changes rather than looking only at a final number.
When it changed. Where it changed. What changed around it. What was affected.
Sophisticated industrial timeline visualization showing a production operation changing over several time periods. Highlight performance deterioration with related asset states, events and process changes along the timeline. 16:9.
Once the relevant relationships are visible, teams can investigate the factors contributing to the outcome.
The objective is not simply to identify an abnormal metric. It is to understand the chain of events and dependencies that produced it.
From symptom → relationship → cause → impact.
Clean visual root-cause investigation through a manufacturing system. Start with an outcome, trace backward through several connected processes and assets, identify a specific contributing event or constraint. 16:9.
Understanding the system creates a better basis for intervention.
Teams can use the model and analysis to focus attention on:
The goal is not more analysis. The goal is better action.
Executive industrial decision visualization. A manufacturing operation with several possible intervention points, highlighting one area where the largest operational impact can be achieved. 16:9.
ValueTwin is designed as a continuous analytical loop.
the operation
the data
the system
the problem
the operation
As the organization learns more about the operation, the model can evolve with it.
Premium circular industrial intelligence loop with five stages: Model, Connect, Explore, Diagnose, Improve. Integrated with a real manufacturing operation. 16:9.
We'll help determine what data, model and analysis are needed to investigate it.
