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Intelligent Sequence Optimization Method for Hole Making Operations in 2M Production Line

机译:2M生产线孔制作孔操作智能序列优化方法

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This paper is concerned with the optimization of the tool path in a production line consisting of two machine tools. Existing computer - numerical control (CNC) time estimation methods are based either for a single machine or a single operation. As current methods don't illustrate the necessity of the multiple operations with more than one machine, this paper presents a new method for CNC machining time estimation which predicts the optimal tool path sequence with minimal time for a 2M production line. The optimized sequence is determined by employing the most reliable hybrid method i.e., Genetic Algorithm (GA). Attention was focusing on the hole making operations where a hole may need multiple cutting tools to get the process finished. Each of the machines can do certain set of operations. So the non-productive time between two machines should be minimized and it is obtained by this intelligent sequence optimizer. This proposed technique is developed on a modified travel salesman problem algorithm with preceding constraints. The work also introduces a computational program based on this methodology. The numerical simulation conducted in this research shows that the proposed approach is feasible and practical. It is beneficial especially in real-time manufacturing process outlining and scheduling multiple systems.
机译:本文涉及由两种机床组成的生产线中的工具路径的优化。现有的计算机数控(CNC)时间估计方法基于单个机器或单个操作。由于目前的方法没有说明具有多个机器的多个操作的必要性,本文提出了一种用于CNC加工时间估计的新方法,其预测具有2M生产线的最小时间的最佳工具路径序列。通过采用最可靠的混合方法I.,遗传算法(GA)来确定优化的序列。注意力专注于孔制造操作,其中一个孔可能需要多种切削工具来获得过程完成。每个机器都可以执行一组操作。因此,应最小化两台机器之间的非生产时间,并通过此智能序列优化器获得。该提出的技术是在具有前述约束的修改的旅行推销员问题算法上开发。该工作还基于该方法引入了计算计划。本研究中进行的数值模拟表明,该方法是可行和实用的。它有益于实时制造过程概述和调度多个系统。

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