Simio Digital Twin Simulation Software offers a comprehensive and agile platform for discrete event simulation, designed to solve complex operational problems by precisely replicating real-world process behavior. With a legacy spanning over 46 years in simulation innovation, Simio released its fourth-generation, fully object-oriented, data-generated, and data-driven platform in 2009, continuously advancing its capabilities to overcome previous generation hurdles. The platform is fast, scalable, adaptive, and adept at utilizing enterprise data while seamlessly integrating with operational environments. It is widely adopted globally, taught in hundreds of universities, and trusted by thousands of users across diverse industries. The Simio platform is engineered to support Industry 4.0 digital transformation journeys by creating Intelligent Adaptive Process Digital Twin models. These models combine discrete event simulation with AI, resulting in unparalleled intelligence capable of generating highly optimized solutions with lightning-fast efficiency. Simio Process Digital Twins automatically adapt to changes in enterprise data, including resources, materials, routings, labor, and schedules. They accurately replicate the physical behavior of operational processes for systems of any size and complexity, enabling users to design, optimize, predict, and prescribe current and future system performance. Simio supports a broad range of application workstreams, including Simulation & Analysis, Process Design & Optimization, Advanced Planning and Scheduling (APS), Shop Floor Orchestration, and Design-to-Operate Process Management. Simio Process Digital Twins eliminate guesswork by providing detailed insights into operational process behavior, offering a low-risk, cost-effective way to design efficient new processes or analyze and optimize existing ones. They function predictively as powerful decision support tools to improve operational outcomes or prescriptively as execution management applications for near real-time process optimization. The architecture serves as a centralized knowledge base, capturing system constraints, business rules, and detailed logic for accurate replication of mission-critical operations. These scalable and reusable models are excellent operational reference tools for evaluating and ensuring the impact of transformation and improvement initiatives.

Features & Benefits

• Versatile
  • Simio Process Digital Twins can be used for both greenfield and brownfield applications, to design new or improve existing operational processes. They can simulate and analyze behavior occurring in the present or at any time in the future, and help understand a single mission-critical process or a complex network of processes that occur at a single site or across multiple sites.
• Data-Generated
  • Simio provides a traditional point-and-click user interface alongside an intuitive data-generated, data-driven approach for developing and executing Process Digital Twin models. A data-driven approach accelerates model development for complex scenarios, facilitates model reuse, and supports the scaling of models to new sites, multi-site applications, and end-to-end supply chains.
• Object-Oriented
  • Build comprehensive Process Digital Twin models without coding using intelligent out-of-the-box object libraries, and easily expand these libraries through subclassing and creating custom user- and industry-specific objects. Any Simio model can be used as an object in another Simio model, facilitating reuse and hierarchical modeling.
• Templates
  • Simio provides a library of application-specific templates containing predefined objects, process logic, and data schemas to jump-start Process Digital Twin model development for complex operational processes. Each template is customizable to fit any user-specific requirements.
• AI-Enabled
  • Simio supports training, testing, and embedding Deep Neural Network agents into Process Digital Twin models, along with bidirectional interaction with Machine Learning algorithms to enhance model intelligence, optimize results, and reduce execution run times. Simio also supports the import and direct use of Machine Learning regression models in the ONNX format.
• Scalable Deployments
  • Simio offers a range of deployment options, including cloud-based solutions, to broaden the reach and utility of Process Digital Twins for stakeholders across the enterprise — both internal and external — for applications such as Simulation, Planning & Scheduling, and Shop Floor Orchestration.
• Integrations
  • Simio’s architecture is built on an extensive integration framework that includes bidirectional database connectors, support for Excel and CSV, Web APIs for cloud, enterprise system, and IoT device integrations, and support for C#, Python, and SQL.
• 3D Visualization
  • Simio Process Digital Twin models are true digital twins in both operational accuracy and visual detail. With 3D, GIS, and VR capabilities, users have powerful visualization features at their disposal, in addition to extensive data reporting, Gantt charts, and dashboards to validate model behavior and showcase operational performance.
• Stakeholder Management
  • Process Digital Twins make detailed Gantt charts and interactive dashboards available to all stakeholders, both internal and external to the business, by publishing the results on a centralized cloud platform. This ensures that all stakeholders are updated and aligned to synchronize execution management and decision support.
• Simulate & Optimize
  • A Process Digital Twin offers a low-risk method to simulate, analyze, and optimize business transformation and process improvement proposals, such as CapEx initiatives, process changes (e.g., automation, layout adjustments, labor schedules), all aimed at enhancing efficiency and achieving the expected ROI.
• Decision Support
  • Process Digital Twins empower and enhance decision support by utilizing enterprise data from sources like ERP, MES, SCP, and IoT to predict and prescribe operational behavior and performance in complex environments such as factories, warehouses, and supply chains.
• Debottlenecking
  • Skilled labor shortages, SKU proliferation, and market demand fluctuations are among the factors that put pressure on manufacturing, warehousing, and supply chains, causing bottlenecks in critical operations. Process Digital Twins are a powerful resource for understanding and eliminating these bottlenecks.
• Planning & Scheduling
  • Process Digital Twins accurately replicate the physical behavior of processes, resulting in actionable schedules that include all resource and material requirements, and respect both the physical constraints of the system and the standard operating rules and detailed execution timelines.
• Third-Party Synchronization
  • Process Digital Twin models can incorporate all third-party service providers and value-added processes, including OEM schedules, to ensure the synchronization of all time-critical tasks and services, which helps avoid synchronization delays, overtime, and expediting to meet the global execution schedule and satisfy business KPIs.