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Linear Constraint Programming for Cost-optimized Configuration of Modular Assembly Systems

机译:线性约束规划,用于模块化组装系统的成本优化配置

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In this paper, we develop an optimization model for providing a logical layout for reconfigurable assembly systems from a library of available equipment modules. The design problem addresses the challenges in equipment selection to build workstations and subsequently the entire assembly system. All the available equipment modules are assumed to be modular and each of them retains a subset of skills (capabilities). The set of all available equipment modules, their skills, mode of physical connectivity (ports) and costs are known. The objective is to minimize the overall equipment cost without violating their physical connectivity (ports) constraints and the precedence constraints of the assembly process requirements. The analysis of the problem and the state-of-art review steered us to the following: (1) the design problem is very closely related to the assembly line balancing problems; (2) a few Genetic Algorithm (GA) based approaches are already available for the capital cost optimization of multi-part flow-line (MPFL) configurations that includes the operational precedence constraints; (3) to our knowledge, this is the first work to combine the equipment physical connectivity constraints with task precedence in order to provide a valid and optimal configuration solution. A formalized mathematical model is developed to select suitable subsets of equipment modules and group them into workstations to construct an optimal logical layout. A number of scenarios based on an industrial case study are simulated and the results are analysed to evaluate the performance of the proposed models.
机译:在本文中,我们开发了一个优化模型,该模型可从可用设备模块库中为可重新配置的装配系统提供逻辑布局。设计问题解决了在选择设备以构建工作站以及随后整个装配系统方面的挑战。假定所有可用的设备模块都是模块化的,并且每个模块都保留了一部分技能(功能)。所有可用设备模块的集合,其技能,物理连接方式(端口)和成本是已知的。目的是在不违反设备的物理连接性(端口)约束和组装过程要求的优先约束的情况下,将总体设备成本降至最低。对问题的分析和最新的综述将我们引向以下方面:(1)设计问题与装配线平衡问题密切相关; (2)一些基于遗传算法(GA)的方法已经可用于多部分流线(MPFL)配置的资本成本优化,其中包括操作优先权约束; (3)据我们所知,这是将设备物理连接性约束与任务优先级结合在一起以提供有效和最佳配置解决方案的第一项工作。开发了形式化的数学模型,以选择设备模块的合适子集,并将它们分组到工作站中以构建最佳的逻辑布局。模拟了基于工业案例研究的多种场景,并对结果进行了分析,以评估所提出模型的性能。

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