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

机译:2M生产线制孔作业的智能顺序优化方法

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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:本文涉及由两条机床组成的生产线中刀具路径的优化。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。由于当前的方法不能说明使用多台机器进行多次操作的必要性,因此本文提出了一种新的CNC加工时间估算方法,该方法可预测一条最短时间的2M生产线的最佳刀具路径序列。通过采用最可靠的混合方法,即遗传算法(GA)来确定最佳序列。注意集中在制孔操作上,在该操作中,一个孔可能需要多个切削工具才能完成加工。每台机器都可以执行某些操作。因此,应将两台机器之间的非生产时间减至最少,并通过此智能序列优化器获得该时间。这项拟议的技术是在具有先前约束的改进旅行商问题算法的基础上开发的。该工作还介绍了基于此方法的计算程序。数值模拟表明,该方法是可行的。这在实时制造过程概述和计划多个系统中特别有用。

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