News in Opus Suite 2022

Below follows the highlights in Opus Suite presented at the beginning of 2022.

New features

Consumables 

OPUS10 has no restrictions or limitations on the type or number of parts that are included in the optimization. But often users end up in situations where they are unsure what items to include in their models. Questions like “should we really compare the investment of a full engine to things like nuts and bolts?” are quite common. The typical answer has been to include the parts that influences the system availability. But such an approach might leave out considerable impacts on the support cost over the entire life length. To tackle this, it is now possible to include consumables in the model. Consumables are things like liquids, lubricants, nuts, bolts, etc. that are required when performing certain maintenance tasks, but are handled differently than traditional items. In OPUS10, the way that consumables are accounted for is that the consumption in terms of both costs and quantities are calculated and included in the results, but they are not included in the stock optimization. This feature makes it possible to get a more detailed and inclusive life support cost, without increasing the complexity of the model by representing the product breakdown to the very last level.  

 

Maintenance while in service

The classic scenario in SIMLOX is that a system aborts its current operation and returns for maintenance as soon as an event requiring critical maintenance occurs. It has previously also been assumed that  systems need to return  to specified locations to access spare parts from the support organization. However, there are situations where such assumptions limit the ability to accurately model a scenario. Some types of systems carry spares along, to replace parts that requires maintenance, and some also have the capability to perform repair tasks on certain components on board, while still being in service. 

In SIMLOX, users now have the possibility to describe and simulate such scenarios. It is possible to model that maintenance is performed directly on board a system while it is still in service. In the results section, this new feature makes it possible to tell whether systems undergo maintenance during operations or not through the use of the new result states "fully capable" and "not capable". This is handled in SIMLOX by the introduction of a new modeling element called onboard station which can be connected to a certain system deployment. The appropriate maintenance capability, stock, resources etc. can then be assigned to that onboard station.

 

Degradation and recovery of operability  

Complex systems are often able to operate in several different capacities to perform certain types of assignments or services. The readiness to perform with a certain capacity typically varies over time. For example, a system may start off with a full capability to perform any type of operation or mission which it is designed for. But during a scenario, the ability to perform some of these assignments may degrade due to failures, scheduled maintenance, shortages etc. If, or when, the required maintenance can be performed, the system regains its capacity.  
In SIMLOX, different types of operational capabilities are described as operational modes and from now on it is possible to define priorities for different operational modes for a certain mission. Depending on what modes the system is considered capable of at a certain point in time, the one with the highest priority will be performed. Therefore, the operational mode can change during service as failures occur that degrades the operability, and as maintenance is performed to regain it. In the result presentation users can review how much the time systems are operating in different operational modes. This functionality becomes even more powerful when used in combination with the SIMLOX capability described above; “Maintenance while in service”. 

Utilization-based operations 

Operations are now described both in OPUS10 and SIMLOX with a utilization profile. Each profile is defined as a total utilization in operating hours per year which can be split up into missions. Utilization rates can be defined per calendar time or any other user-defined operational parameters. This means that systems that belong to different organizational units may use the same utilization profile. In OPUS10, the utilization profile is converted to an average utilization like before, but in SIMLOX this new functionality offers an easy way of describing basic operations, e.g. an 8 hour daily operation.

Profile view updates

Previously, the profile view in SIMLOX has been able to visualize explicit operation profiles. With the latest release comes the possibility to also view the simplified definition of operations, which has been introduced with the new utilization-based description of operations described above. 

Structure of groups

The group concept in Opus Suite has been improved further by allowing one group to be entered as a member of another group. This makes it possible to create structures of groups in a flexible manner. It is always the union of members that are considered within a group, which makes it possible to, for example, include one individual object in two different groups and still combine those two groups in a common, overlying, group.

Performance enhancements for simulation of functional breakdown scenarios

In SIMLOX there has been significant improvements on the performance for scenarios using functional breakdowns (FBD’s). These improvements shorten the run-time which enhances the applicability and effectiveness of the analyses, especially for complex scenarios. 

Refined features

Self-supported deployments with unscheduled start times  

The concept of self-supported deployments with unscheduled start times is introduced in OPUS10. A self-supported deployment is when a system can carry stock and perform certain types of maintenance "on itself". This is modeled by using the concept of an on-board station for which the capability to perform maintenance is defined analogously to ordinary stations. Such deployments only rely on the standard support organization for brief periods of time. A key feature in this model is that when the system leaves the home base for a mission, the risk of not being fully stocked is considered. With this assumption comes that missions are called on an irregular basis, i.e. the start times are unscheduled, and the operating time is typically greater than the time at the home base. A similar model has been available in previous versions as well, then under the name of Autonomous Mission.  

 

Time dependent failure rates

The modeling of time variations in the failure rate (FRT) is reintroduced in SIMLOX. Now, failure rate changes are described in a separate table where it is defined as a change factor based on the initial value. The change factor is applied starting from a specified time and remains active until a new change is introduced. This feature makes it possible to consider aspects like an increased risk of failure due to ageing components.