Opus Evo – Tactical Optimization of Dynamic Scenarios

Opus Evo is a game changing addition to Opus Suite, introducing new, unique capabilities within logistics support optimization. The first release of Opus Evo provides two main capabilities - tactical optimization of the procurement of spare parts and support equipment for defined budget periods and optimization of maintenance capabilities for international missions and other deployed operations.

Opus Suite users and supportability engineers worldwide strive to deliver the best possible analyses and recommendations to support decision making - in contexts and situations that are often both complex and vital for overall success. Systecon’s aim with Opus Evo is to further empower these efforts by adding new, powerful analysis capabilities to the broad range already available in Opus Suite - giving decision makers the data-driven analysis that they need for critical decisions throughout the system life cycle.

Discover more below about the two main capabilities currently available:

A strong complement to OPUS10, SIMLOX, and CATLOC…
The groundbreaking approach of Opus Evo provides new flexibility and application areas within logistics support optimization, primarily in dynamic scenarios with short to medium time frames. This makes Opus Evo a strong complement to the optimization, simulation, and cost analysis capabilities already available in OPUS10, SIMLOX, and CATLOC.

…using the same scenario model
For current users of OPUS10 or SIMLOX, it is easy to get started with Opus Evo, as all the analysis tools in Opus Suite use the same data model. Opus Evo optimizations can use the scenario models already built in OPUS10 or SIMLOX, as well as their input and output data.

Opus Evo – one optimization engine with several modules
Opus Evo utilizes cutting-edge, heuristics-based mathematical optimization together with simulation and analysis to provide a new range of powerful strategic and tactical decision-making tools. Read more about the Opus Evo optimization approach here.

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Read more about the first two Evo-modules currently available below. 

Deployed Operations Planner - powered by Opus Evo

The Deployed Operations Planner (“EVO-DOP”) puts unique new capabilities in the hands of defense logistics commanders, program managers and supportability engineers. This Evo-module provides an incomparable ability to maximize mission success rate and abilities to quickly restore readiness for deployed operations*, by ensuring the appropriate logistics responsiveness and minimizing downtime. Use EVO-DOP to optimize and tailor the combination of logistics support equipment, spares and personnel to ship to a current or planned deployed operation.*units deployed away from home base with limited or no support from the mother organization 

Use Opus Evo Deployed Operations Planner to:

  • Determine the optimal assortment of spares and support resources to bring along, given the expected duration and mission profile of a deployment
  • Operational optimization for maximal mission success rate and readiness during the deployment - or any other defined effectiveness targets
  • Optimize with respect to one or several restrictions, for example transport volume, weight and/or budget.

Game changing approach
Opus Evo Deployed Operations Planner uses the same data model as the rest of Opus Suite, and the same trusted and proven simulation core as SIMLOX. This combination of agile modeling, cutting edge simulation, and evolutionary algorithms really shifts the boundaries for what can be accomplished. For one, it means that EVO-DOP optimization is not restricted to steady state scenarios and average values. Just like SIMLOX, it can accommodate detailed descriptions of the operations, technical systems and logistics resources, and account for dynamic variables and parameters that vary over time, such as system utilization, resource availability. The result? A unique capability to determine the optimal mix support resources for any deployed scenario, short or long.

Other application areas for EVO-DOP
The powerful combination of evolutionary algorithms and simulation in EVO-DOP also provides the following capabilities and application areas:

  • Tactical optimization of spare parts while fully accounting for the impact of redundancies and functional block diagrams. This can be done for any desired time frame, which is highly useful as the impact of redundancies and need for spares is quite different for short vs. long term scenarios.
    Consider, for example, a naval scenario where each ship can be    considered a system of systems that typically include complex redundancies - and where the cost, volume and weight efficiency trade-offs can be optimized to achieve the target mission capability for each expected scenario (and for each individual sub-system).
  • Multi-faceted trade-offs of any kind of support resources, to determine the optimal combination of spare parts, maintenance equipment technicians, mobile repair facilities, etc. given the available funding and/or transportation volume and weight.

Contact us to learn more, or to book a demonstration of Opus Evo


Tactical Logistics Support Procurement Optimizer - powered by Opus Evo

The Tactical Logistics Support Procurement Optimizer (“EVO-LPO”) makes it possible to determine how to optimally use the funding for a defined time period (e.g. an annual budget) to purchase spares and support equipment, maximizing the ability to reach performance requirements. A key strength (and unique capability) in this Evo-module is the ability to factor in the procurement lead time of each spare part / support equipment and varying budget constraints, so that each procurement occurrence is optimized to provide the best possible contribution to fleet performance and readiness.

Use Opus Evo Tactical Logistics Support Procurement Optimizer to:

  • Determine the optimal use of the support and maintenance budget for the upcoming budget period, and preliminary planning for future budget periods.
  • Decide not only what to buy, but when to buy which spares (and other support equipment), given their respective lead times, in order to meet performance targets, readiness and capability requirements and other priorities.
  • Decide how to adapt your procurement planning based on increases/decreases to allocated budget, in order to get the highest possible fleet performance and/or meet other operational requirements.

Optimal use of defense budgets
The capabilities provided by EVO-LPO is more relevant than ever for defense forces in NATO and allied nations, currently investing in stronger defense. The key question is how to put these significant additional defense budget funding to optimal use. How to make the best possible use of tax-payers money. How to maximize defense capability, readiness and robustness in both the short and long term? Such decisions are vital, and with EVO-LPO they can be based on solid decision support.

…as well as maintenance and support budgets in other industries
Outside of defense, the best use of taxpayer money is of course equally relevant in other industries, for example rail, power generation or mining. Virtually any organization operating a fleet of advanced technical systems that wants to ensure that the maintenance and support budget is used optimally to contribute to the performance of its fleet of trains, wind turbines or mining drills.

Tactical optimization accounting for lead times
As explained above, EVO-LPO makes it possible to account for long lead times for certain parts, and their impact on fleet availability in the short and long term. To give a simplified example, it may seem obvious to order a spare component with a three year lead time, but that should be traded off against spares with shorter lead times, higher failure rate, etc. that may hence contribute to fleet availability sooner. It all depends on the specific scenario and its requirements, priorities and limitations. This tactical optimization is a very strong complement to the strategic optimization of spares assortments and maintenance concepts provided by OPUS10.

Game changing approach
EVO-LPO uses the same trusted and proven simulation core as SIMLOX, and the very comprehensive and adaptable Opus Suite RDM data model that our users are familiar with from OPUS10 and SIMLOX. This combination of cutting edge simulation, evolutionary algorithms and flexible modeling is key to the game changing capabilities of Opus Evo. For one, it means that EVO-LPO is not limited to steady state scenarios and average values. Just like SIMLOX, it can accommodate very detailed descriptions of the operations, technical systems and logistics resources, and account for dynamic variables like variations in e.g. system utilization, resource availability and lead times. This provides a unique capability to determine the optimal procurement of spares and support resources for any scenario and budget.

The flexible approach in EVO-LPO makes it possible to select different optimization targets, for example minimize fleet downtime, maximize mission time fraction, fleet availability, service levels or mission capability.

Contact us to learn more, or to book a demonstration of Opus Evo



More on the Opus Evo optimization approach

Opus Evo utilizes meta-heuristic evolutionary algorithms in combination with simulation and/or conventional mathematical optimization. This approach gives a lot of freedom and flexibility, both when selecting which variables to optimize, when defining one or several optimization targets (performance, cost, volume, weight, etc), and finally when it comes to including all the relevant details, dynamics, dependencies and sophistications of a given scenario (system configuration, support organization, operational profile, etc).