Abstract: Methods and devices for optimizing the climb of an aircraft or drone are provided. After an optimal continuous climb strategy has been determined, a lateral path is determined, in particular in terms of speeds and turn radii, based on vertical predictions computed in the previous step. Subsequently, computation results are displayed on one or more human-machine interfaces and the climb strategy is actually flown. Embodiments describe the use of altitude and speed constraints and/or settings in respect of speed and/or thrust and/or level-flight avoidance and/or gradient-variation minimization, and iteratively fitting parameters in order to make the profile of the current path coincide with the constrained profile in real time depending on the selected flight dynamics (e.g. energy sharing, constraint on climb gradient, constraint on the vertical climb rate). System (e.g. FMS) and software aspects are described.

Abstract: A computer-implemented method includes a processor extracting data and metadata from a process model, where the process is comprised of activities and the metadata is associated with each activity. The processor generates at least one user story for at least one activity, where the at least one user story includes an estimate attribute reflecting a predicted timeframe for completion of at least a portion of the at least one activity. The processor updates the model to reflect the at least one user story and displays the updated model as a project plan in a project management interface on a computing resource. The processor assigns a resource to the at least one user story and dynamically updates the estimate attribute of the at least one user story to reflect a new predicted timeframe, calculates impacts to the process and displays the impacts and the new predicted timeframe in the project management interface.

Abstract: A computer-implemented method includes a processor extracting data and metadata from a process model, where the process is comprised of activities and the metadata is associated with each activity. The processor generates at least one user story for at least one activity, where the at least one user story includes an estimate attribute reflecting a predicted timeframe for completion of at least a portion of the at least one activity. The processor updates the model to reflect the at least one user story and displays the updated model as a project plan in a project management interface on a computing resource. The processor assigns a resource to the at least one user story and dynamically updates the estimate attribute of the at least one user story to reflect a new predicted timeframe, calculates impacts to the process and displays the impacts and the new predicted timeframe in the project management interface.