کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5481188 | 1522097 | 2017 | 39 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modelling of energy demand from computer numerical control (CNC) toolpaths
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
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چکیده انگلیسی
It is important to accurately model the total electrical energy requirements in order to compare and select the least energy consumption toolpath in a manufacturing process. To enable this goal in this study, a feed axes energy demand model (which incorporates the weights of feed axes, machine vice, and workpiece) proposed in previous work by the authors was integrated and used to refine the energy consumption models for machine tools to analytically estimate the power and processing time, and hence energy required to execute a CNC toolpath. Furthermore, an algorithm for establishing energy prediction software with regards to numerical control (NC) codes was developed based on the proposed energy consumption model. The NC-code based analytical model and energy prediction software were both validated by undertaking slot milling of a 2D half bottle toolpath. Results show that shorter linear path lengths (i.e. G01) and circular path segments (i.e. G02 and G03 codes) were highly energy intensive. This is because for short length segments, the maximum feedrate may not be reached due to constraints imposed by acceleration and deceleration; the weights carried take a higher share of the load, and therefore increase the inertia effects on the drive. Thus, energy intensity in machining could be significantly reduced by selecting toolpaths with longer linear path segments. The knowledge obtained in this study would enable machining engineers to predict the electrical energy for toolpaths and hence enable selection of toolpaths for reduction of electrical energy demand in machining.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Cleaner Production - Volume 157, 20 July 2017, Pages 310-321
Journal: Journal of Cleaner Production - Volume 157, 20 July 2017, Pages 310-321
نویسندگان
Isuamfon F. Edem, Paul T. Mativenga,