Fuzzy Petri net based reasoning for the diagnosis of bus condition

A bus maintenance system in a transport organization is discussed. The bus fleet consists of different types of buses operating on international, intercity and local lines. The fleet should have good corrective and preventive maintenance. Periodic inspections and preventive maintenance activities must be conducted following the manufacturer's recommendations for the warranty to be valid and for the equipment to operate properly. Daily requests for maintenance resources vary depending on stochastic factors, which are out of the control of the operations manager. The paper presents a programme developed by the use of a fuzzy Petri net which is aimed to help a maintenance manager to predict the needs for maintenance resources, as well as the time duration of maintenance activities. The prediction is based on the use of incomplete and vague information on the overall condition of a bus. By using CPN Tools software, a colored Petri net that performs the process of fuzzy reasoning is developed. The final assessment of the bus overall condition is drawn from the data and information about the bus and its exploitation in the previous period. The reasoning process consists of five phases, twelve attributes and 45 rules.