An Agent-Based Social Simulation Approach to Task Allocation in Aircraft Maintenance Teams

Abstract

Tighter profit margins and rising aircraft complexity are currently driving the need for aircraft maintenance organizations to increase efficiency. Many organizations believe that digitization is key for improving operational performance. Digitization of the task allocation process at a large aircraft maintenance organization did unexpectedly not lead to increased efficiency. Anthropological research concluded that the implemented technologies did not accommodate for the social nature of teamwork. This research studies the relationship between the social aspects of teamwork and the performance of task allocation methods in aircraft maintenance. An Agent-Based Social Simulation model has been created and simulated for different types of task allocation methods as well as different types of teams. The presented model includes social influence relations between team members and decision-making based on trust in others' performance. The model has been simulated for a case study of an Airbus A310 main landing gear replacement. Independent teams provided the best performance using a mediated feedback automated negotiation method. The most beneficial results for compliant teams were obtained through task allocation by the team lead. Social teams presented significantly better results for voting than for other task allocation methods. The combination of socially oriented mechanics and task allocation by voting provided the most advantageous task execution performance for all simulations. It was shown that, in line with the wisdom of crowds theory, diversity in initial trust levels in combination with shared trust among mechanics over time increased collaborative task allocation performance.