Out-of-order enabled operating system for uncertain planning, scheduling and execution in aviation maintenance

Maintenance has long been a concern in manufacturing, both in the production and product-service phases. As a type of large product, aviation maintenance produces a collection of services to ensure that aircrafts or aircraft systems, components, and structures meet airworthiness standards. Planning, scheduling, and execution (PSE) is important for maintenance systems to optimize resource utilization and job sequencing through decision-making at different time cycles. However, stochastic uncertainty always exists, affecting the stability of the entire maintenance process. Therefore, in this study, which was inspired by operating systems (i.e., Windows, Android, etc.) for processing uncertain user actions with high efficiency, an out-of-order enabled operation system in aviation maintenance (OoO-AMOS) is designed to mitigate the influence of uncertainties that exist in the PSE procedure. Two key components, namely, thread manager and resource manager, are proposed at the kernel level of the OoO-AMOS. The concept of out-of-order (OoO) is deployed for the thread manager to dynamically select the optimal order sequence based on task dependencies and feasibility. A finite state machine (FSM) model is integrated as the operation validation mechanism to formulize the resource states and their transitions. Finally, a case study is conducted to evaluate the effectiveness of the proposed OoO-AMOS. The results show that OoO-AMOS presents significant advantages over traditional approaches. In uncertain environments, the total setup time was reduced by more than 55 %, whereas the maintenance makespan, average order tardiness, and hangar turnover rate achieved improvements of more than 22 %, 31 %, and 23 %, respectively. • Out-of-order enabled operation system in aviation maintenance is designed for PSE process. • Out-of-order is deployed to dynamically select the optimal job sequence. • Finite state machine-based operation validation mechanism formulizes the resource states.