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Operational Simulation & Optimization

Test Manufacturing Decisions Before You Make Them

The most expensive manufacturing decisions are the ones made without understanding their downstream impact. With Aegis, contextualized manufacturing data can continuously inform Simio-powered digital twin simulation, creating a living representation of how the operation actually runs. Simio can also be used independently to evaluate layouts, automation, staffing, capacity, and production changes virtually, so teams can validate decisions before committing resources or making changes on the factory floor.

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Capital Decisions Deserve More Than a Spreadsheet Estimate

Expanding capacity, redesigning a production line, introducing automation, or launching a new product all require significant investment. Yet many manufacturers still evaluate these decisions using spreadsheets, static assumptions, or one-time engineering studies that can't account for the variability of real production.

Averages hide the variability that actually determines whether a plan works. A layout that looks fine on paper can create a new bottleneck the moment real order variability, staffing gaps, or equipment downtime enter the picture.

Common challenges include:

  • Capital projects get approved on static assumptions that don't reflect real operating variability.

  • Leadership has no consistent way to compare competing investment options before committing budget.

  • Automation and layout changes are difficult to validate until they're already installed.

  • Continuous improvement initiatives are hard to prioritize without knowing which change will have the largest impact.

From Real Production Data to a Living Digital Twin

Simio Process Digital Twin lets teams evaluate layouts, automation, staffing, capacity, and production flow virtually before making changes. It can be used independently or with FactoryLogix, where contextualized production data continuously informs the digital twin so it reflects how the operation actually runs, not just static assumptions. 

Simio Process Digital Twin can leverage FactoryLogix's contextualized manufacturing data, including products, routings, resources, work in process, and material status, to create a digital twin that reflects actual operations instead of simplified engineering assumptions.

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The Business Case for Testing Decisions First

Simio Process Digital Twin helps manufacturers evaluate strategic decisions before committing capital, while FactoryLogix provides the contextualized manufacturing data that keeps simulations aligned with operational reality. Whether used independently or together, manufacturers can compare scenarios, reduce implementation risk, and make more informed decisions with greater confidence.

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Investment Decisions

Justify Capital Spend With Evidence, Not Estimates

Compare competing capital projects, a new line, an automation cell, a facility expansion, against the same simulated baseline before budget is committed. Leadership sees how each option performs under real order variability instead of a best-case average, so approval decisions rest on evidence rather than optimism.

  • Data-grounded comparisons between competing investment options

  • Reduced risk of funding a project that underperforms

  • Consistent baseline for leadership sign-off across proposals

  • Clear before-and-after performance evidence for board reporting

  • Fewer capital decisions based on best-case assumptions

  • Budget confidence backed by simulated outcomes, not estimates

Built to Validate Decisions Before They Cost Money

The Technology Behind Confident Capital Decisions

Unlike traditional simulation software that requires engineers to manually build and maintain models, Simio Process Digital Twin can leverage FactoryLogix's contextualized manufacturing data to create a digital twin that stays aligned as manufacturing changes.

Digital Twin Simulation

Model the operation using real production data instead of averages, then validate assumptions and compare alternatives in a risk-free simulated environment.

Production Flow Analysis

Identify bottlenecks, queues, and WIP buildup across the operation, surfacing constraints that are difficult to see in day-to-day reporting.

Capacity Planning

Evaluate equipment investments, staffing levels, and facility expansion decisions against realistic demand and variability before committing budget.

Scenario Evaluation

Compare new products, new equipment, layout changes, and automation strategies side by side, using the same operational baseline for a fair comparison.

Operational Optimization

Balance throughput, cycle time, and resource utilization across the operation, identifying the changes that will actually move the numbers that matter.

Continuous Improvement Validation

Test proposed improvements in simulation before implementation, reducing the risk that a change that looked good on paper becomes a disruption on the floor.

Strategic Decisions Across the Operation

Simulation for the Decisions That Are Hard to Undo

Some manufacturing decisions are expensive to reverse. Simio Process Digital Twin helps manufacturers evaluate those decisions against operational reality before equipment is purchased, layouts are changed, or production is disrupted.

The Benefits of Digital Twin Simulation

Testing a decision before making it changes the risk profile of a manufacturing investment, at every level of the organization.

Confidence Before Commitment

Whether the decision is a new line, layout change, or capacity investment, Simio Process Digital Twin gives planners and leadership a shared, data-grounded view of how the operation is likely to respond before decisions become permanent.

Reduced Capital Risk

Compare investment options against the same operational baseline before committing budget, instead of relying on separate estimates that are hard to compare fairly.

Fewer Surprises After Go-Live

Validate layout, staffing, and process changes in simulation first, so the gap between the plan and the floor is smaller when it counts.

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Related Insights & Resources

Discover how manufacturers use digital twin simulation to improve capacity planning, validate operational changes, and make more confident decisions before they reach the factory floor.

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FAQ's

The questions operations and planning leaders ask most about digital twin simulation and Simio Process Digital Twin.

A digital twin is a simulation model of a production operation built from real operational data, used to test decisions like layout changes, staffing plans, or new equipment before they're implemented on the floor.

Ready to See the Impact Before You Commit to It?

See how Simio Process Digital Twin helps manufacturers evaluate production changes before they reach the factory floor. 

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