Flexible and scalable field service with condition base maintenance models for simulating large scale scenarios

Field service planning and scheduling research focuses on providing solutions to scenarios in which personnel travel between multiple locations carrying out different tasks specific to the field where they work. However, studying”what-if” activities in these scenarios is challenging for researchers, who have to deal with the impact on client service agreements, preferences of technicians when tasks are assigned, or unexpected faulty units. Therefore, simulation techniques are widely used to experiment and understand some critical aspects of workforce scheduling. Unfortunately, to mimic reality a high number of parameters are required within simulation models, raising scalability issues when the number of technicians, activities, and units increase over certain limits. This work¹ presents a flexible simulation model to address field service planning and scheduling in large scale scenarios. The evaluation proves that the model executes in reasonable time for environments that consist of hundreds of thousands of locations in which technicians must perform diverse numbers of activities.