Companies involved in the transportation rarely optimize the way they care for vehicles. All too often vehicle maintenance, repairs and routine work is treat as a reactive, panic driven process. Not only does this cost the business money through not being able to have full capacity when they need it, but it also fundamentally leaves the client experience at risk.
Vehicle maintenance scheduling needs to shift from the realm of last minute panic to a demand-aware optimization problem. This proposal takes a smarter approach to Scheduled Maintenance by centering scheduling recommendations around a Hybrid decision making architecture. Scheduling decisions now begin with a foundation of compliance requirements, and then narrowing down from the compliance time frame into a few suggested dates and times which minimize operational impact and ensure scheduling occurs in the projected low-times of vehicle demand.