Evaluation of prognosis solutions for wind turbine using multi agent simulation of maintenance business

In the maintenance service business, introducing IoT solutions is an expected strategy to improve the maintenance efficiency. However, it is difficult to predict in advance the quantitative effects of IoT solutions on the overall business. This study proposes the simulation approach to quantitatively evaluate the improvement effect of IoT solutions using the multi agent modeling for maintenance business. This model includes the behavior of maintenance workers and is characterized by evaluating the resource workload. The effectiveness of the proposed approach is verified in the case study of a dispatch-type maintenance service for wind turbines. The availabilities of wind turbines are compared in two prognosis solution introduction stories with six cases. The change trends in availability by introducing prognosis solutions can be explained by both the reduction in asset failures and the resource status of maintenance workers. In the simulation result, the introduction of anomaly prediction without changing the current maintenance policy resulted in an increase in workload and rather worsened availability, which indicates that the proposed method can assess the risk of reduced availability. Also, the availability improved significantly when combined with a change in maintenance policy, such as omitting periodic inspections. These results indicate that the proposed method can evaluate the synergistic effects of prognosis solutions and maintenance policy changes.