多台数控加工中心的生产调度决策技术,可加工时间受限

IF 1.4 4区 工程技术 Q4 ENGINEERING, MANUFACTURING
Jianzhong Qiu, Jun Wu, Xi Chen, Bingyan Zhao, Yan Fang
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引用次数: 0

摘要

数控加工中心的刀具寿命统计模块通常会将刀具的使用时间与程序的运行时间联系起来,导致刀具空闲时间被记录为刀具寿命损失。这往往会导致过早更换刀具。为了提高多个加工中心的排程精度,我们利用主轴电流的变化来区分刀具负载和空闲时间。最初,我们收集了加工中心的实时数据,并采用了三参数 Weibull 分布法,以 1.351 (A) 作为阈值来区分刀具空闲和加载状态。随后,我们提出了一种计算刀具可用时间的改进方法,从而能够更精确地估算刀具的剩余工作寿命。我们还根据工具的可用时间为多个数控加工中心设计了一种调度方法。最终,实证试验表明,刀具平均利用效率提高了 10%,加工中心的生产率提高了 12.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Production scheduling decision-making technology for multiple CNC machining centers with constraints on serviceable time

Production scheduling decision-making technology for multiple CNC machining centers with constraints on serviceable time

The tool’s life statistics module in CNC machining centers typically associates tool’s usage time with the program’s running duration, leading to the tool idle time being logged as a loss in tool life. This often triggers premature tool replacements. To enhance scheduling accuracy across multiple machining centers, we leverage spindle current variations to discern between tool loads and idle periods. Initially, real-time data from the machining center was gathered, and we employed the three-parameter Weibull Distribution method, using 1.351 (A) as the threshold to distinguish between idle and loaded tool states. Subsequently, we proposed a refined method to calculate the tool’s available time, enabling a more precise estimation of its remaining operational lifespan. We further devised a scheduling approach for multiple CNC machining centers based on the tool’s availability time. Ultimately, empirical trials exhibited a 10% increase in average cutting tool utilization efficiency and a 12.5% enhancement in machining center productivity.

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来源期刊
Journal of Scheduling
Journal of Scheduling 工程技术-工程:制造
CiteScore
3.80
自引率
10.00%
发文量
49
审稿时长
6-12 weeks
期刊介绍: The Journal of Scheduling provides a recognized global forum for the publication of all forms of scheduling research. First published in June 1998, Journal of Scheduling covers advances in scheduling research, such as the latest techniques, applications, theoretical issues and novel approaches to problems. The journal is of direct relevance to the areas of Computer Science, Discrete Mathematics, Operational Research, Engineering, Management, Artificial Intelligence, Construction, Distribution, Manufacturing, Transport, Aerospace and Retail and Service Industries. These disciplines face complex scheduling needs and all stand to gain from advances in scheduling technology and understanding.
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