汽车制造中经验教训与问题关联的智能解决方案

L. Ionescu, N. Ionescu, E. Stirbu, N. Rachieru, C. Stirbu, A. Mazare
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引用次数: 0

摘要

本文提出了一种在工业(汽车)中实现的解决方案,该解决方案通过一个由积累的经验教训组成的数据库进行查询,并根据当前问题进行更新。这是使用具有深度学习的智能算法-人工神经网络(DL-ANN)完成的。该解决方案属于在企业中实施工业4.0技术的策略:在行业中使用智能技术。利用经验教训数据库来确定某些当前问题和解决或减少其影响的解决办法是企业经常采用的一种战略。使用这种策略的挑战与技术团队制定问题的方式以及工厂不同分支之间可能出现的语言差异有关。因此,在若干情况下,虽然所吸取的经验教训数据库包含了相应的问题,但无法正确地确定,甚至根本无法确定。本文提出的解决方案通过对数据库中的问题进行智能识别来解决识别问题。本文还介绍了一个应用该解决方案的案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Solution for Associating Problems with Lessons Learned Used in Automotive Manufacturing
The paper presents a solution implemented in industry (automotive) through which a database consisting of accumulated lessons learned is consulted and updated with the current problem. This is done using an intelligent algorithm with deep learning - artificial neural networks (DL-ANN). The solution falls within the strategies of implementing Industry 4.0 technologies in the enterprise: the use of intelligent technologies in the industry. The use of database of lessons learned to identify certain current problems and the solutions to solve or reduce their impact is a strategy frequently found in enterprises. The challenge in using this strategy was related to the way the problems are formulated by the technical team as well as the possible linguistic differences that occur between the different branches of the factory. Thus, in several situations, although the lessons learned database contained the respective problem, it could not be identified correctly or even at all. The solution proposed in this article solves the identification problems through an intelligent problem recognition in the database with lessons learned. The paper also presents a case study where the solution was applied.
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