نوع مقاله : علمی - پژوهشی
نویسندگان
1 دانشجوی دکتری، گروه مهندسی معدن، دانشکده معدن،نفت و ژئوفیزیک، دانشگاه صنعتی شاهرود
2 استاد، گروه مهندسی معدن، دانشکده معدن،نفت و ژئوفیزیک، دانشگاه صنعتی شاهرود،
3 استادیار، گروه مهندسی معدن، دانشکده فنی، دانشگاه بین‌المللی امام خمینی(ره)، قزوین
4 استاد، دانشکده تکنولوژی و ایمنی، دانشگاه شمالگان ترومسو نروژ
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
The Remaining Useful Life (RUL) valuation of mining machinery is a principal to ensure the production/output and customer satisfaction in the mining zone. In many cases, it may be of attention to know the expected value of the remaining life of the item before it fails from an arbitrary time that known RUL. The system's failure is also evaluated with the reliability index, which describes up-times. An individual unit's reliability during field use is essential in many mining equipment applications. This index, especially in industrial systems, and being affected by the internal condition also affects operating environmental conditions. For example, the loader performance in cold weather will be different from that of warm, which will affect the machine's reliability and thus the RUL. In reliability engineering, operating environmental conditions are considered "Risk factors or Covariates". Therefore, in this paper, an approach is proposed first to analyze the system's reliability considering covariates' effect and then estimate the RUL for different scenarios. The proportional hazard model was used in reliability analysis to be realistic and take the operational influencing factors in calculation. Methods are presented for calculating the reliability function and computing the RUL as a function of the current conditions to guarantee the desired output. The remaining useful life estimation of a Komatsu PC-1250 from the Sungun copper mine was evaluated as a case study of this approach. Systems operating environmental factors such as shift, dump-truck kind, rock kind, … (known as covariates) are assumed to influence covariate in this context. As a result, the Weibull proportional hazard model was fitted to describe the failure behavior, and the RUL of four selected scenarios was evaluated. Presented results can be used, e.g., for developing operational performance, planning of maintenance activities, spare parts provision, and the profitability of the owner of an asset.
کلیدواژه‌ها [English]
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