Systecon North America  

Juno Beach,  FL 
United States
  • Booth: 1981

Systecon and their Opus Suite of tools have been optimizing some of the most complex Life Cycle Management projects in over 20 countries worldwide. We are the market leader in predictive analytics, with the DoD embracing our tools to solve complex problems, including US Navy, USMC, OSD, and the F35 Joint Strike Fighter. We work across the entire product life cycle, relying on methods that have been tested and refined for over 40 years and analyses using our proprietary, global market-leading Opus Suite software. For our customers, this means more efficient operations, controlled costs, and most importantly: decisions based on facts. Systecon embraces the latest in technology and continues to advance its position as marketplace leader, having been selected in every head to head comparison of tools for the past 15 years.


  • AI tool: Tactical Augmented Optimization (TAO)
    TAO together with SIMLOX is a unique AI-powered tool for scenario simulation that enables analysis of expected performance over time given a certain support solution and operational scenario.<br /><br />...

  • Tactical Augmented Optimizaion (TAO) - AI-enabaled CBM+ tool

    TAO together with SIMLOX is a unique tool for scenario simulation that enables analysis of expected performance over time given a certain support solution and operational scenario.

    TAO with SIMLOX offers superior insight into tactical and strategic mission capability and the ability to prepare for planned operations.

    Tactical Machine Learning

    Our tactical machine learning algorithm utilizes an unsupervised approach.  This provides an ability to “learn” how the vehicle is being operated or more precisely, what are the “current” mission requirements and what performance variables are impacting availability today.

    Regime Identification

    Regime Identification is at the core of the Systecon solution. The algorithm independently identifies and catalogs operational regimes at the individual vehicle level. This approach is in stark contrast to historical deep dives of past performance requirements to predict future failure modes and apply them in aggregate across an entire fleet of vehicles.

    Predictive Analyses

    As regimes are identified for each vehicle using telemetry and on-board system data (pressure, torque, temp, etc) normal operation across all sensors is identified for each known regime. This provides an unprecedented level of context and insight into future and past component failures and moves this analysis across the ecosystem. This improves all areas of support from future acquisition, engineering, maintenance, and supply chain functions.


    Supply Chain

    • Reduce False Demands
    • Limit No Fault Found
    • Optimized Sparing
    • Automated CS&S Planning
    • Provide “Just In Time” Processes


    • Reduce Man Hours
    • Predictive Maintenance Alerts
    • Reduce Unscheduled Maintenance
    •  Increased Root Cause Identification

    Mission Impacts

    • Increased Operational Readiness
    • Higher Mission Success Rates
    • Reduce Training Timelines
    • Optimize O&M Budgets
    • Pure Fleeting Capabilities

    Engineering Analysis

    • Dynamic FRACAS
    • Individual Vehicle FRACAS
    • Safety of Flight Profiling
    • Configuration Management
    • Digital Twin Generation
  • Opus Suite
    Opus Suite supports the mathematical representation of complex systems and subjects the resulting models to simulated real-life or hypothetical operational parameters to optimize performance and logistics support solutions...


    -Assess the capability of a system fleet and its support solution to handle dynamic operational scenarios, peak loads, resource limitations, etc.

    -Design support solutions and dimension resources like depots, equipment, staff, transports, etc.

    -Identify and eliminate weak links, bottle-necks and reasons for system down-time.


    -Enables higher operational availability, increased sustainability and more efficient support solutions.

    -Assesses robustness of support solutions and the risk of not being able to fulfill the operational requirements.

    -Makes it possible to set up and evaluate PBL-solutions* based on trustworthy decision support (Verified & Validated by UK MOD and used by customers world wide)

    -Can model any dynamic operational scenario, any technical system with multi-level break-down structures and any complex asymmetrical multi-level support organization

    -Easy and efficient to use with fast calculations (even large cases optimized in seconds)

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