Aerogility to forecast powerplant shop visits for SAS
Courtesy SAS
Aerogility will prepare optimised workscopes, initially focusing on powerplant shop visits and operational costs.
Arising from research into AI and autonomous systems, Aerogility’s intelligent agents function as ‘actors’ in virtual model-driven simulations that represent SAS’ entire MRO operation. The software-as a service (SaaS) solution automatically generates optimised maintenance plans based on a multi-agent model of the SAS fleet and operations.
With Aerogility, SAS fleet planners can handle complex planning factors quickly and easily. The transparency of the simulations means the analytics and scheduling results are explicable and understandable – an important factor in safe and trusted decision-making. By comparing different plans and strategies, fleet planners can optimise the maintenance and engineering programs for the SAS fleet, achieving the wider goals of overall efficiency and sustainability.
SAS has a large and diverse fleet, which includes Airbus A319, A320, A320neo and A321 aircraft, as well as Boeing 737s, meaning the maintenance requirements are complex. SAS wanted a solution that could not only handle powerplant shop visit scheduling, but also help in the phasing out of 737s and introduction of new Airbus aircraft. SAS is committed to reduce its climate affecting impact and software that results in fewer shop visits will contribute in doing so.
Phil Cole, Civil Aviation Business Manager at Aerogility, added: “The key feature in the latest version of Aerogility is a functionality that enables the planner to define the workscope for each powerplant unit. Aerogility provides predicted utilisation statuses for each of the three main modules, enabling the planner to make an informed decision and customise the workscope accordingly.”
Following the successful deployment of this powerplant shop visit forecasting solution, SAS is now planning to extend its use of Aerogility to cover heavy base maintenance scheduling.
