Variation analysis of automated wing box assembly
Variation analysis of automated wing box assembly
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DOI：
10.1016/j.procir.2017.02.034
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
O. Bakker;Atanas A. Popov;S. Ratchev
中科院分区：
文献类型：
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作者：
O. Bakker;Atanas A. Popov;S. Ratchev
制造过程的可变性是高附加值行业关注的主要问题。制造小批量，在某些情况下，一批一批是一个非常昂贵的过程，对制造操作、工装和夹具及其自动化和信息供应水平有特定要求。自动化的目标是降低成本，平衡日益减少的熟练车间工人数量。然而，这些小系列通常是包含复杂和符合要求的部件的产品，而且通常还包含大量部件和组件。这种小批量、高价值生产的自动化可能是一项艰巨的任务。每个过程都有自己的关键参数，这些参数要求在一定的公差范围内，以确保产品质量，例如装配配合特征的尺寸和位置。尺寸质量保证通常通过过程中测量或当前设置中的某些关键特性(KCs)的测量来完成，但可能必须在制造过程中的仅测量步骤中使用特殊设置。每个制造阶段都会引入由夹具、已用工艺等不确定性引起的误差。这些误差将在下游阶段传播，甚至会加剧在后一个阶段引入的误差。提出了一种新的通用方法，用于在智能工厂环境中使用变化流分析(SOV)，例如可演化装配系统(EAS)框架。这项研究是通过一个飞机翼盒总成的EAS演示器的简化案例来演示的。翼盒组件及其KCs使用形式表示法来描述。采用SOV模型对装配过程进行建模和仿真。然后对仿真结果进行分析，以预测、控制和最小化由工艺和设备中的不确定性引起的误差传播。
Manufacturing process variability is a major issue of concern in high value industries. Manufacturing small batches and in some cases batches of one is a very expensive process with specific requirements for manufacturing operations, tooling and fixturing and their level of automation and informatics provision. The automation targets cost reduction and a counterbalancing of the ever lower numbers of skilled shop floor workers. However, these small series typically are products that contain complex and compliant parts, and often also a high number of parts and components. The automation of this type of low-volume high-value production can be a daunting task.Each process has its own key parameters that are required to be within a certain tolerance band in order to ensure product quality, such as e.g. the dimensions and location of assembly mating features. Dimensional quality assurance is typically done with in-process measurement, or the measurement of certain key characteristics (KCs) in the current setup, but a special setup may have to be used in a measurement-only step in the manufacturing process. Each manufacturing stage introduces errors stemming from uncertainties in the fixturing, used processes etc. These errors will propagate in downstream stages and can even worsen errors introduced in the latter stages.The paper presents a new generic methodology for the use of stream of variation (SoV) analysis within a Smart Factory environment such as the Evolvable Assembly Systems (EAS) framework. The research is demonstrated using a simplified case study of one of EAS demonstrators for an aircraft wing box assembly. The wing box assembly and its KCs are described using formal representation. The SoV model is applied to model and simulate the assembly process. The simulation results are then analysed to predict, control and minimise the error propagation coming from uncertainties in process and equipment.