Accurate energy consumption modeling is an essential prerequisite for sustainable manufacturing. Recently, cutting-power-based models have garnered significant attention, as they can provide more comprehensive information regarding the machining energy consumption pattern. However, their implementation is challenging because new cutting force coefficients are typically required to address new workpiece materials. Traditionally, cutting force coefficients are calculated at a high operation cost as a dynamometer must be used. Hence, a novel indirect approach for estimating the cutting force coefficients of a new tool-workpiece pair is proposed herein. The key idea is to convert the cutting force coefficient calculation problem into an optimization problem, whose solution can be effectively obtained using the proposed simulated annealing algorithm. Subsequently, the cutting force coefficients for a new tool-workpiece pair can be estimated from a pre-calibrated energy consumption model. Machining experiments performed using different machine tools clearly demonstrate the effectiveness of the developed approach. Comparative studies with measured cutting force coefficients reveal the decent accuracy of the approach in terms of both energy consumption prediction and instantaneous cutting force prediction. The proposed approach can provide an accurate and reliable estimation of cutting force coefficients for new workpiece materials while avoiding operational or economic problems encountered in traditional force monitoring methods involving dynamometers. Therefore, this study may significantly advance the development of sustainable manufacturing.
The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00370-1
Kai-Ning Shi
,
Ning Liu
,
Cong-Le Liu
,
Jun-Xue Ren
,
Shan-Shan Yang
,
Wei Chit Tan
. Indirect approach for predicting cutting force coefficients and power consumption in milling process[J]. Advances in Manufacturing, 2022
, 10(1)
: 101
-113
.
DOI: 10.1007/s40436-021-00370-1
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