{"title":"基于NSGA-II的可重构制造传输线多目标优化方法:一个案例研究","authors":"M. Ali, A. AlArjani, M. A. Mumtaz","doi":"10.14743/apem2023.1.461","DOIUrl":null,"url":null,"abstract":"In response to the wide range of customer demands, the concept of reconfigurable manufacturing systems (RMS) was introduced in the industrial sector. RMS enables producers to meet varying volumes of demand over varying time periods by swiftly adjusting its production capacity and functionality within a part family in response to abrupt market changes. In these circumstances, RMS are made to swiftly reconfigure their Reconfigurable Machine Tools (RMTs). RMTs are designed to have a variety of configurations that may be conditionally chosen and reconfigured in accordance with specific performance goals. However, the reconfiguration process is not an easy process, which entails optimization of several objectives and many of which are inherently conflictual. As a result, it necessitates real-time monitoring of the RMS's condition, which may be achieved by digital twinning, or the real-time capture of system data. The concept of using a digital replica of a physical system to provide real-time optimization is known as digital twin. This work considered a case study of discrete parts manufacturing on a reconfigurable single manufacturing transfer line (SMTL). Six manufacturing operations are required to be performed on the parts at six production stages. This work uses the Digital Twin (DT) based approach to assist a discrete multi-objective optimization problem for a reconfigurable manufacturing transfer line. This multi-objective optimization problem consists of four objective functions which is illustrated by using DT-based Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The innovative aspect of the current study is the use of a DT-based framework for RMS reconfiguration to produce the best optimum solutions. 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引用次数: 0
摘要
为了响应广泛的客户需求,可重构制造系统(RMS)的概念被引入工业领域。RMS使生产商能够满足不同时期的不同数量的需求,通过快速调整其生产能力和功能,以响应突然的市场变化。在这种情况下,RMS被要求快速重新配置其可重构机床(rmt)。rmt被设计成具有各种配置,这些配置可以根据特定的性能目标有条件地选择和重新配置。然而,重新配置过程并不是一个简单的过程,它需要优化几个目标,其中许多目标本身就是相互冲突的。因此,需要实时监测RMS的状态,这可以通过数字孪生或实时捕获系统数据来实现。使用物理系统的数字副本来提供实时优化的概念被称为数字孪生。本工作考虑了在可重构单制造传输线(SMTL)上离散零件制造的案例研究。需要在六个生产阶段对零件进行六个制造操作。这项工作使用基于数字孪生(DT)的方法来辅助可重构制造传输线的离散多目标优化问题。该多目标优化问题由四个目标函数组成,并利用基于dt的非支配排序遗传算法- ii (NSGA-II)进行了说明。当前研究的创新之处在于使用基于dt的RMS重构框架来产生最佳的最佳解决方案。生成的实时解决方案将极大地帮助决策者在可重构制造生产线中选择合适的实时最优方案。
A NSGA-II based approach for multi-objective optimization of a reconfigurable manufacturing transfer line supported by Digital Twin: A case study
In response to the wide range of customer demands, the concept of reconfigurable manufacturing systems (RMS) was introduced in the industrial sector. RMS enables producers to meet varying volumes of demand over varying time periods by swiftly adjusting its production capacity and functionality within a part family in response to abrupt market changes. In these circumstances, RMS are made to swiftly reconfigure their Reconfigurable Machine Tools (RMTs). RMTs are designed to have a variety of configurations that may be conditionally chosen and reconfigured in accordance with specific performance goals. However, the reconfiguration process is not an easy process, which entails optimization of several objectives and many of which are inherently conflictual. As a result, it necessitates real-time monitoring of the RMS's condition, which may be achieved by digital twinning, or the real-time capture of system data. The concept of using a digital replica of a physical system to provide real-time optimization is known as digital twin. This work considered a case study of discrete parts manufacturing on a reconfigurable single manufacturing transfer line (SMTL). Six manufacturing operations are required to be performed on the parts at six production stages. This work uses the Digital Twin (DT) based approach to assist a discrete multi-objective optimization problem for a reconfigurable manufacturing transfer line. This multi-objective optimization problem consists of four objective functions which is illustrated by using DT-based Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The innovative aspect of the current study is the use of a DT-based framework for RMS reconfiguration to produce the best optimum solutions. The produced real-time solutions will be of great assistance to the decision maker in selecting the appropriate real-time optimal solutions for reconfigurable manufacturing transfer lines.