No abstract

A properly implemented maintenance management system has an impact at different levels. Maintenance is defined as the set of actions to maintain a property in a specified state. The unavailability of the spare parts required, to carry out the maintenance intervention, causes an extension of the inactivity time of the installation. On the contrary, an excessive stock of spare parts confines enormous capital and entails an enormous cost of ownership. According to the literature already made, we have directed in our work to propose a model of joint management of maintenance and spare parts based on stochastic-deterministic batch Petri networks. We studied this model by simulation using a graphical interface dedicated to the graphical tool used. So, we present, in this paper, the analytical study of the model by defining the performance indicators and viewing the influence of system parameters on these indicators. The main stages of the analytical study are developing the μ-marking graph, the associated Markov process which gives the associated transition matrix, and the definition of performance indicators using the probability distribution of the states. We deal with an application of the analytical evaluation of the proposed model. We end this article with an analysis and synthesis.

The spare parts inventory is a necessity to ensure the continuity of services. Unwanted service interruptions caused by failures can have serious consequences for human and financial levels. Analytical models begin to look to the random nature of inventory problems. Despite the existence of a wide variety of inventory management models, inventory management of spare parts is a major challenge for organizations. Some authors have integrated the principle of risk of shortage in their different models based on probabilistic and graphical models. This article is in the form of a literature review on models of spare parts management. In this article, we have presented first methods of identification and classification of parts, the approaches of estimation and identification of spare parts needs. Afterwards, we have moved to probabilistic models for spare parts management, among these models, there are models that take aim minimize and master the risk of shortages.

The need to have a stock of spare parts in a production company is very important in order to contract a continuity of service assurance. The costs of the stock are the costs of ownership, the costs of purchases and the costs of breaking the stock. In summary, the estimation of the needs of the stock is done mostly through quantitative methods while minimizing the costs.In this paper, we will first present our Bayesian model developed taking into account the obsolescence risk that is related to the life of parts, in order to determine the combination of new and recycled parts in quantities. After, we will expose some of the decision results of the simulation in order to clarify the operation of the bayesian networks. Finally, we will compare our model with the existing reference model and the bootstrap method for the purpose to see the influence of the parameters considered.

Maintenance management is an orderly procedure to address the planning, organization, monitoring and evaluation of maintenance activities and associated costs. The maintenance management allows to have an efficient tool either to the management of the preventive or curative activity, an optimization of the production tool, and finally a follow-up of the costs and the performances. A good maintenance management system can help prevent problems and damages to the operating and storage environment, extend the life of assets, and reduce operating costs.In this paper, we will first present our model on the joint management of spare parts and maintenance. We will do a simulation study of our model, presented in the first section of this paper. The results of this study are presented in the second section through the presentation of the influence of certain parameters of the model on the operation of the system under consideration. This study carried out on the graphical interface of Matlab, which is one of the performance evaluation techniques. It allows to visualize the variations and anomalies which can be reached in the system considered as an overcoming of the repair of the machines by the unforeseen breakdowns.