مدل کاهش استرس تعمیر و نگهداری پیشگیرانه برای یک واحد تحت محیط پر تنش

We develop a preventive maintenance (PM) model for a unit operated under stressful environment. The PM model in this paper consists of a failure rate model and two cost models to determine the optimal PM scheduling which minimizes a cost rate. The assumption for the proposed model is that stressful environment accelerates the failure of the unit and periodic maintenances reduce stress from outside. The failure rate model handles the maintenance effect of PM using improvement and stress factors. The cost models are categorized into two failure recognition cases: immediate failure recognition and periodic failure detection. The optimal PM scheduling is obtained by considering the trade-off between the related cost and the lifetime of a unit in our model setting. The practical usage of our proposed model is tested through a numerical example.

Some units are exposed to a stressful environment, the stressful environment causes unit failure more often than in general or recommended environment. For example, the PDP-TV monitors installed at the platform of subway stations for providing the transportation information is operating under too much dust and trembling. The dusty and trembling condition in a platform may cause the malfunction of monitors more often than in normal conditions because the dust inside of monitors interrupts heat radiation and the trembling loosens part connections. For a unit under stressful environment, of necessity, various preventive maintenance (PM) activities for reducing the environmental stress are employed to prevent failure and prolong the unit lifetime. The PDP-TV monitors at the platform of subway stations are also maintained by periodic cleaning and screw-tightening the parts inside of them. The aim of this paper is to propose a PM model for a unit under stressful environment. In a stressful operating condition, the unit deteriorate more intensively and fail more often than a normal condition [1] and [2]. Some PM activities are employed to protect the unit from the stressful environment. Those are especially effective when the unit operates under a stressful environment since those work for making the operating condition less stressful. In this paper, we focus on a PM model that reduces the stress of an operating environment but does not change the inherent failure rate of a unit. The proposed PM model of this paper consists of a failure rate model and two cost models to determine the optimal PM scheduling which minimizes a cost rate. The failure rate model handles the maintenance effect of PM using improvement and stress factors. The improvement factor expresses the degree of improvement by PM, and the stress factor measures the stress of operation environment. The cost models are developed under age-dependent periodic PM policy, in which a unit is preventively maintained at each fixed time point. The cost models are categorized into two failure recognition cases: immediate failure recognition and periodic failure detection. The optimal PM scheduling which is minimizing cost rate is obtained under considering the related cost and parameters in our model setting. This paper is organized as follows. Section 2 presents the related research literatures and introduces the assumption and the outline of our proposed PM model. 3 and 4 describe the failure rate model and two cost models, respectively. We show some numerical examples of the optimal PM scheduling determination given a Weibull failure distribution in Section 5. Section 6 provides the concluding remarks.

PM of this paper reduces the stress placed on the unit so that the lifetime of the unit can be extended. The proposed PM model consists of a failure rate model and two cost models to determine the optimal PM scheduling. Our failure rate model reflects the maintenance effect of PM so that the failure rate of a unit under stressful environment can be lowered to the failure rate under normal environment. In addition, we developed two cost models under two failure detecting case: immediate failure recognition and periodic inspection for failure detecting. We provided numerical examples to implement our proposed models. In the numerical analyses, we observed the following features of stress-reducing PM. First, the cost parameters (C M, C R, C I, C B), especially the breakdown penalty cost (C B), affect the unit more strongly than the improvement factor (ρ ), the stress factor (k ) for the optimal PM scheduling determination. Second, the optimal scheduling (View the MathML sourceTI⁎, View the MathML sourceTM⁎) tends to be insensitive to the stress factor when the stress factor becomes over a certain threshold level. Third, the improvement factor has a relatively weak effect on the optimal maintenance scheduling, while the improvement factor significantly affects the optimal maintenance scheduling. This paper can be referred to plan an appropriate PM scheduling for a unit under stressful environment. In particular, the proposed failure rate model can provide a quantitative way of analysis when PM can control the stressful environment elaborately. As a future work, the PM model in this paper needs to be extended to incorporate block PM policy [27] under which more than two units are simultaneous maintained.