An innovative approach to maintenance for a bus fleet

This thesis work is the result of an internship at Arriva Italia Srl, that is a local public transport company and owns a fleet of about 2500 buses. Specifically, the internship has been carried out in Turin, where the company owns a fleet of about 215 buses. Among the various departments of the company, the section where I operated was the Technical Area, which focuses on vehicle maintenance. To better understand, it could be useful to introduce the definition of maintenance, according to legislation UNI 13306:2018, which states that "Maintenance is the combination of all technical, administrative, and managerial actions, during the life cycle of an entity, intended to maintain it or return it to a state in which it can perform the required function”. Regarding the goal of the thesis, currently the company performs maintenance activities in a planned or corrective manner; it means that interventions are planned in advance and in parallel the technicians take action when unexpected failures occur. In the following chapters, these types of maintenance will be discussed in detail with a focus on their respective advantages and disadvantages, as well as when to implement a certain type of maintenance instead of another. As technology and the quality of components and lubricants evolve, there is a tendency to leave behind the old maintenance plans with their fixed, pre-set deadlines and move towards predictive maintenance. The aim of this thesis is to renew the maintenance plans used so far in the company in order to reduce vehicle downtime and costs and to implement a predictive approach. Predictive maintenance means having systems that can use AI (Artificial Intelligence) and algorithms to process data collected on board in order to estimate the remaining life of the component and then take action just before the component fails. Data collection can be carried out by means of telediagnostic systems that collect the data of interest through the CAN line. The goal of this thesis was also to implement telediagnostic systems on a limited family of Arriva buses and monitoring of the data collected in order to analyze the boundary conditions of the occurrence of a failure and plan an action in a predictive manner. The future perspective is to replace maintenance plans imposed by the manufacturer or with fixed deadlines and to adopt only a predictive policy that step by step is able to plan maintenance activities.