Smart operations require the ability to generate alternative plans whenever a change in operations occurs in an unplanned manner. Alternate maintenance plans, in a highly dynamic context such as airline operations, require the ability to foresee small developments in terms of labor allocation, repairable items, and downtime, when and where they were not previously scheduled. In addition to being able to cause the disruption of the air transport network and consequent financial losses, it causes loss of trust in the company brand. Prescriptive maintenance is a potential technological response when using Artificial Intelligence to suggest alternative plans promptly so that decisionmakers can reduce the impact on air operations. This paper proposes a framework for the construction of an integrated prescriptive maintenance solution that is certifiable by using auditable methods and extensible to complex systems of other industries. The adoption of prescriptive maintenance not only enhances the use of health management systems, widely available in modern aircraft fleets that have the potential to predict the remaining useful life of items of interest, but also allows identifying more than one response alternative to conflicts of interest in the conduction of the smart operations of air transport companies.

PurposeA framework is being developed to help Integrated Electronic Technical Publications (IETP) consultation inside and outside the aviation maintenance hangar. The expected results are the reduction in time to access the desired IETP and to assist mechanics while performing maintenance tasks using voice recognition.Design/methodology/approachThe work is being conducted based on literature review and consultation with mechanics from the aviation industry, through questionnaires. The development will be made through study cases by building a core search engine and mobile applications to support the mechanics during the maintenance activities.FindingsThe identified problem in small maintenance shops and defence organizations suggests that IETP are not entirely accessible before and during the maintenance activity. Such organizations suffer from information and communications technology (ICT) low infrastructure capability and demand access to multiple IETP databases as they usually support different aircraft. To have access to the IETP through voice assistant application will help mechanics to access the IETP, including when they would be with dirty hands and having difficulty in using mobile devices with touch displays.Originality/valueThe framework being developed will give mechanics the ability to quickly find any existing IETP to support its maintenance task at any time and in any place with low demanding for ICT infrastructure. The architecture will support different applications, and the identified priority is for IETP viewers to the most demanding functionality of specification ASD S1000D. This approach could also help in troubleshooting activities since COVID-19 brought new demands for the social distancing for mechanics.

Manufacturing and assembling aircraft require hundreds of different machines for various process applications. The machines have different complexity and often different ages; however, they have to ensure a higher precision than other industrial fields. Recent technology advancement in maintenance approaches offers a wide range of opportunities to provide performance and availability. The paper discusses how the maintenance technologies applicable to the various machines need to be appropriately supported by a production environment, called “ecosystem”, that allows their integration within the process and their synergy with the operators. (1) A background analysis of the aircraft production environment is offered. (2) A possible framework for designing a proper ecosystem 4.0 for integrating maintenance activities with design solutions and data gathering is provided. (3) A case study based on the assembly line of specific aircraft is adopted for testing the validity of the framework. (4) Finally, a discussion highlights the critical points of the research, underlying future work.