Abstract
Maintaining high efficiency of using the fleet of public mass transport vehicles puts many challenges ahead of the operator. Among them, when planning periodic operational activities, the operator should take into account the assessment of possible unexpected vehicle failures and the costs of their removal under the so-called corrective maintenance. Due to the random nature of vehicle breakdowns, knowledge about stochastic processes is necessary to maintain their efficient and safe operation. The research problem formulated in the title meets these needs. Therefore, the costs of corrective maintenance of vehicles are modelled, i.e. the costs that are not included in the scheduled maintenance costs and are not related to preventive maintenance. The costs of corrective maintenance and the costs of replacement of damaged parts are unexpectedly created at random moments of operating means of transport, usually between scheduled maintenance. Due to the variety of failure processes of individual parts of the vehicle, the methods and applications of stochastic modelling for simple failures modelled by the Poisson process are presented in this paper. The basis for the application of the presented methods is to identify those parts of the vehicle that are damaged in accordance with this process. The assessment of parameters of failure processes of individual vehicle parts is made on the basis of the operational database of a homogeneous fleet of vehicles operated for 5 years. The operational database is dynamically updated with new events. On the basis of actual data on corrective maintenance of a distinguished group of damaged parts of vehicles, the possibilities and limitations of practical applications of the Poisson process to assess the risk of incurring costs in the further process of fleet operation were shown.
Highlights
The design and construction of complex technical objects that meet high requirements in terms of energy consumption, cost-consumption, ecology, safety, availability and functionality require obtaining extensive, and detailed knowledge concerning, among others, forecasting the frequency of failures occurring during their use [2, 5, 18, 21, 22, 26]
In order to minimise the costs of removing failures and ensuring the safety of using a technical object, the designer needs to know why and which adverse events may occur during the operation phase of the object
This knowledge is necessary for optimisation of the life cycle cost (LCC) of the object and is made available by the constant flow of information from the various phases of the existence of a technical object understood in the Agile Systems categories [14, 21, 27]
Summary
The design and construction of complex technical objects that meet high requirements in terms of energy consumption, cost-consumption, ecology, safety, availability and functionality require obtaining extensive, and detailed knowledge concerning, among others, forecasting the frequency of failures occurring during their use [2, 5, 18, 21, 22, 26]. Despite the fact that all the requirements regarding i.a. operational availability of the technical object are taken into consideration during the designing phase, random failures are unavoidable during its operation These failures are removed as part of unscheduled corrective maintenance (CM), which reduces availability and generates additional, unplanned operating costs. The authors present the results of research on the applicability of this stochastic process to modelling the processes of losing operational availability of vehicles and to assessment of the risk of incurring the corrective maintenance costs.
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