Hu, L and Peng, C and Evans, S and Peng, T and Liu, Y and Tang, R and Tiwari, A (2017) Minimising the machining energy consumption of a machine tool by sequencing the features of a part. Energy, 121. pp. 292-305.
Full text not available from this repository.Abstract
Increasing energy price and emission reduction requirements are new challenges faced by modern manufacturers. A considerable amount of their energy consumption is attributed to the machining energy consumption of machine tools (MTE), including cutting and non-cutting energy consumption (CE and NCE). The value of MTE is affected by the processing sequence of the features within a specific part because both the cutting and non-cutting plans vary based on different feature sequences. This article aims to understand and characterise the MTE while machining a part. A CE model is developed to bridge the knowledge gap, and two sub-models for specific energy consumption and actual cutting volume are developed. Then, a single objective optimisation problem, minimising the MTE, is introduced. Two optimisation approaches, Depth-First Search (DFS) and Genetic Algorithm (GA), are employed to generate the optimal processing sequence. A case study is conducted, where five parts with 11–15 features are processed on a machining centre. By comparing the experiment results of the two algorithms, GA is recommended for the MTE model. The accuracy of our model achieved 96.25%. 14.13% and 14.00% MTE can be saved using DFS and GA, respectively. Moreover, the case study demonstrated a 20.69% machining time reduction.
Item Type: | Article |
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Subjects: | UNSPECIFIED |
Divisions: | Div E > Production Processes |
Depositing User: | Cron Job |
Date Deposited: | 17 Jul 2017 19:16 |
Last Modified: | 15 Apr 2021 06:31 |
DOI: | 10.1016/j.energy.2017.01.039 |