Reduced order models for uncertainty management and zero-defect control in seal manufacturing

Ismael Viejo Monge, Noelia Alcalá Serrano, S. Izquierdo, Ignacio Conde Vallejo, V. Zambrano, Leticia A. Gracia Grijota
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引用次数: 3

Abstract

Reaching a zero-defect manufacturing is one of the biggest challenge for the current manufacturing industry. One of the barriers to overcome is to handle appropriately the uncertainty propagation across manufacturing lines, that hinder the development of accurate control systems. Within this framework, we introduce a non-intrusive method for uncertainty management that relies on a Monte Carlo approach building on a deterministic parametric real-time simulation model. The real-time simulation model is a Reduced Order Model (ROM) based on a generalized Canonical Polyadic Decomposition. The method is introduced using an industrial test case as demonstrator, namely car door/body seals manufacturing by means of continuous coextrusion of a metal strip and various types of rubber. The resulting model is used to unify uncertainty management of: (i) aleatory and epistemic origin, and (ii) material characterization and process parameters.
减少订单模型的不确定性管理和零缺陷控制在密封制造
实现零缺陷制造是当前制造业面临的最大挑战之一。需要克服的障碍之一是如何适当地处理不确定性在生产线上的传播,这阻碍了精确控制系统的发展。在此框架内,我们引入了一种非侵入式的不确定性管理方法,该方法依赖于建立在确定性参数实时仿真模型上的蒙特卡罗方法。实时仿真模型是基于广义正则多进分解的降阶模型。以一个工业试验案例为例,介绍了一种用金属条与各种橡胶连续共挤制造车门/车身密封件的方法。由此产生的模型用于统一不确定性管理:(i)遗传和认知起源,以及(ii)材料表征和工艺参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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