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A multi-objective decision-making method for machining process plan and an application

delete2020-07-01
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PRE
AI
L
Lishu Lv
Z
Zhaohui Deng *
H
Huijuan Meng
刘涛 cover
刘涛 (Tao Liu)
L
Linlin Wan
DOI:10.1016/j.jclepro.2020.121072delete
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Abstract

Abstract

En 中文
The processing parameters/plan decision of the machine tool can effectively realize the coordinated optimization of production efficiency, processing quality, resource consumption and environmental emissions. However, the current research has problems such as single decision-making objectives, high degree of subjective decision-making, and large error in decision-making results. Against this backdrop, our research proposes a multi-objective decision-making method for a machining process plan. Firstly, the resource consumption and environmental emissions of machining process are analyzed based on an input-process-output (IPO) model. Then, in view of the complex interplay between traditional indicators and environmental impact indicators, we propose a combination weight determined by an analytic hierarchy process (AHP) and the criteria importance through intercriteria correlation (CRITIC) method, which considers subjective weight and objective weight. Thirdly, we set positive and negative reference sequences using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, and the gray correlation and Euclidean distance are used for sorting each experimental group (processing parameters). Finally, an experimental case study is performed on a spindle sleeve made of GCr15, the machining type include turning, grinding, and drilling. The optimal processing parameters are determined to achieve coordinated optimization of resource consumption, processing quality, and production efficiency. (C) 2020 Elsevier Ltd. All rights reserved.
Keywords:
Spindle sleeve
Input-process-output model
Combination weight
Multi-objective decision
Processing parameters
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Journal

Journal of Cleaner Production cover
Journal of Cleaner Production
IF:
10
Papers:
4.7W
Citations:
36.8W

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