دانلود مقاله ISI انگلیسی شماره 93059
ترجمه فارسی عنوان مقاله

دنباله از ویژگی های برای به حداقل رساندن مصرف انرژی غیر برش در ماشینکاری با توجه به تغییر سرعت چرخش اسپیندل

عنوان انگلیسی
Sequencing the features to minimise the non-cutting energy consumption in machining considering the change of spindle rotation speed
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
93059 2017 35 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy, Volume 139, 15 November 2017, Pages 935-946

ترجمه کلمات کلیدی
صرفه جویی در مصرف انرژی، تولید پایدار، چرخش اسپیندل، توالی ویژگی، بهینه سازی کلینیک مورچه،
کلمات کلیدی انگلیسی
Non-cutting energy consumption; Sustainable manufacturing; Spindle rotation; Feature sequencing; Ant colony optimisation;
پیش نمایش مقاله
پیش نمایش مقاله  دنباله از ویژگی های برای به حداقل رساندن مصرف انرژی غیر برش در ماشینکاری با توجه به تغییر سرعت چرخش اسپیندل

چکیده انگلیسی

A considerable amount of energy consumed by machine tools is attributable to non-cutting operations, including tool path, tool change, and change of spindle rotation speed. The non-cutting energy consumption of the machine tool (NCE) is affected by the processing sequence of the features of a specific part (PFS) because the plans of non-cutting operations will vary based on the different PFS. This article aims to understand the NCE between processing a specific feature and its pre- or post-feature, especially the energy consumed during the speed change of the spindle rotation. Based on the developed model, a single objective optimisation problem is introduced that minimises the NCE. Then, Ant Colony Optimisation (ACO) is employed to search for the optimal PFS. A case study is developed to validate the effectiveness of the proposed approach. Two parts with 12 and 15 features are processed on a machining centre. The simulation experiment results show that the optimal or near-optimal PFS can be found. Consequently, 8.70% and 30.42% reductions in NCE are achieved for part A and part B, respectively. Further, the performance of ACO for our specific optimisation problem is discussed and validated based on comparisons with other algorithms.