بهینه سازی تعمیر و نگهداری پیشگیرانه و ارائه قطعات یدکی برای ابزار و ماشین آلات بر اساس شرایط عملیاتی متغیر
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|22439||2009||4 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : CIRP Annals - Manufacturing Technology, Volume 58, Issue 1, 2009, Pages 429–432
The reliability of machine components depends on their operational conditions. In order to maximize this reliability, the preventive maintenance intervals and the provision of spare parts have to be adapted to the individual load collectives. Up to now, there has been for different machine components no comprehensive approach to quantify the effect of load collectives and to adapt the respective actions accordingly. This paper presents a method which calculates the optimal time for preventive maintenance and spare part provision by a stochastic optimization algorithm based on a load-dependent reliability model.
نتیجه گیری انگلیسی
The presented approach aims at analyzing and predicting the load-dependent service-life in order to optimize preventive maintenance intervals and the provision of spare parts under economical aspects. The main focus is on fatigue failures of components which are failures caused by varying loads. This approach helps to achieve a higher accuracy of reliability analysis and prediction by integrating suitable methods and information even if only little field data is available. Within this approach all the necessary parameters are estimated to describe the load-dependent reliability distribution function of a specific component. By using these parameters it is possible to predict the reliability of a component if a certain future load profile can be assumed. This information is combined with economical and logistical aspects such as delivery times or stock strategies for specific components. Cost optimal strategies for the provision of spare parts as well as for scheduling preventive maintenance actions can be developed and evaluated.