Opus Suite 2024
Providing world-class support for LCM analytics is the number one driving force at Systecon. Decades of experience, and a constant presence in the frontline of developing Life Cycle Management, help us maintain the position as the primary choice on a global market. Opus Suite is constantly supported and updated with new versions released regularly. The topics below introduce the main new features presented during the last year, all included in version 2024 of Opus Suite.
New features
- Mission Capability simulation
The new version of Opus Suite introduces a unique and highly useful ability to simulate and assess the mission-capable rate for technical systems over time.
Mission capability / Mission capable rate describes the ability of systems to perform missions of different types, given its current condition. Full mission-capable (FMC) means that a system can perform all of its relevant mission types. For example, aircraft mission types could be search-and-rescue, surveillance, personnel transport, and training. A system can also be partially mission-capable (PMC) when it can perform some of its mission types, or not mission-capable (NMC).
To describe further what this powerful new functionality means, let’s first clarify that it is a complement to the long established key SIMLOX feature to simulate availability and mission success probability over time, given a specific scenario where the intended operations are described as a schedule of missions of different types. Until now, it has however not been possible to assess what is commonly referred to as Mission Capability, which is a way to describe a system’s (or system fleet’s) preparedness for all types of missions that can come up during a scenario. Thus, capturing the readiness and capability to pivot and perform other missions, while performing the anticipated schedule, and also during times when no missions are scheduled. Version 2024 provides users with exactly that ability. It is now possible to capture and predict if and when systems are mission capable, across the entire scenario, and not only during scheduled missions.
With this functionality, users can assess what overall defense capabilities can be expected and ensure that multi-purpose systems - like ships or fighter aircrafts – can meet their complete range of intended capabilities.
This means that SIMLOX now provides an even more comprehensive assessment of the system capability for different operational modes, offering valuable decision support when evaluating readiness requirements and ensuring adherence to specified criteria. For example, the new results can predict if a search and rescue capability of at least 98% can be upheld at all times, or if the capability to perform subsurface warfare missions will be above 80%, and maintained over time, given intended other operations. With the new input data, the user can efficiently capture the different desired system capabilities, and new output data includes new dedicated reports and results on how mission-capable different systems are over time.
Graphical presentations of System Capabilities are accessible both in the traditional and the new SIMLOX result view, where the latter gives a more comprehensive overview and an enhanced visualization of the capability results.- Identification of downtime drivers
In this version of SIMLOX it is possible to get information about which subsystem, or item, that result in a system not being able to perform its desired operation, the so- called "drivers of downtime". Downtime in this context is defined as the time that a system is not capable for an operational mode, due to one or several failures. For example, it is now possible to analyze what component to blame for the system not being able to perform search and rescue operations. Depending on how you want to allocate the blame you can get the answer by subsystem or by items.
- New viewer for Simulation Results
One of the main focuses during the last year has been to make it easier to access and understand the results produced by OPUS10 and SIMLOX. With brand new, complementary, visualizations it is now possible to create customized dashboards tailored to your needs. These dashboards can be saved in their entirety, or simply exported as images or CSV tables.
Users can choose whether to study results with the previous viewer, the new viewer, or both at the same time. After linking a result file to the new view, all graphs are immediately, and automatically, updated once new results are available in the result file.
The goal of the new result viewer is to present results in a more flexible way. For example, the new capability and downtime driver results (see above) can be visualized, and analyzed, more efficiently using the new view.
- Task Results
SIMLOX has now the possibility of presenting fine-grained results for tasks completed during the simulation. These results offer a whole new level of insight into the workload on the support organization, giving additional understanding and analytical capabilities. It also facilitates the understanding and verification of the input model.
Task results are available per combination of task, event, material and time interval. New reports are added and can be configured to provide details, or aggregated results, across all these dimensions.
Task results are obtained per default, but if desired, it is possible to switch off the collection of these results to reduce the need of memory and decrease the size of the output file.
- Probability of utilization of consumables
The calculation of the amount of consumables that are spent when executing a task has been refined. It is now possible to include a probability that a certain consumable will be used. This feature is helpful in situations where a task requires the consumable sometimes..
- Enhanced performance for LORA-XT problems
The time it takes to perform a LORA-XT analysis depends very much on the complexity of the problem at hand. Even for a relatively small model with a limited number of candidates to evaluate the computations can be complex due to the nature of LORA-XT analysis. The time it takes to solve certain LORA-XT problems has until now to some degree been a limiting factor. To address this issue the calculations have been improved to utilize multiple processing units more efficiently. This development has made it possible to solve problems that in previous versions were essentially deemed unsolvable because of the long execution time.
- Filling gaps in the C/E-curve
Thanks to enhancements in the computations the number of points presented on the C/E-curve has increased. This means that the user now has more optimal solutions to choose from to make the best out of a given budget, solutions that were not available in previous versions.
- Filter functions in input tables
For models with a lot of data records it can be tedious to get an overview of how often a certain identifier is referenced within a table. With the new filter functions this is no longer an issue. The user can now easily filter an input table based on an identifier. In OPUS10 and SIMLOX this has been taken one step further making it possible to filter several input tables with respect to an identifier. This enables the user to easily get an overview of the model.
- Resource utilization cost per task
The presentation of costs related to the usage of resources has until now been summarized per resource. These results have been refined and resource utilization costs can now also be presented per maintenance task.
Refined features
- Enhanced model for robbing
Robbing is an alternative way of trying to reduce system down time in case of item shortage. A missing item can be robbed (taken) from another system that is inoperable due to waiting for other replacement items. Robbing is only considered if it speeds up the process of getting the robber system ready while simultaneously not delaying the victim.
In the default setting, robbing is not allowed. To enable robbing, the potential victims are given specific tasks used for the robbing replacement. The robbing activities are now modeled as separate tasks which gives a lot of flexibility since they then may have different duration and resource requirements compared to the standard replacement task.