电机生产4.0 -工业4.0技术在电机制造中的应用潜力

A. Mayr, M. Weigelt, Johannes von Lindenfels, J. Seefried, M. Ziegler, A. Mahr, N. Urban, A. Kühl, F. Hüttel, J. Franke
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引用次数: 31

摘要

工业4.0 (I4.0)伴随着各种技术,为优化电机制造提供了巨大的潜力。然而,工业4.0技术在这一领域的应用几乎还没有得到检验。为了确定电机生产中的I4.0潜力,需要一种结构化的方法,因为各种子过程和生产技术会导致大量可能的组合。因此,本文首先比较了用于识别、选择和实现I4.0用例的不同通用方法。在此基础上,我们提出了一种系统的方法,以挖掘电机生产中的众多I4.0潜力。一方面,用例可以从研究和工业中的应用程序示例和最佳实践产生的当前技术机会中派生出来。另一方面,关键制造过程中的具体问题可以产生新的工业4.0解决方案的应用。本文通过全面概述有前景的应用场景,主要从机会驱动的角度来识别电机生产中的I4.0潜力。除了直接解决电机生产的方法外,还可以从其他应用领域的相关过程中获得概念。通过概述可能最相关的用例的选择来提供示例。结果表明,特别是数据驱动的方法,即数据分析和机器学习,在电机生产中提供了巨大的潜力。作为展望,也可以从问题拉动的角度揭示工业4.0的潜力,补充本文的机会推动的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Electric Motor Production 4.0 – Application Potentials of Industry 4.0 Technologies in the Manufacturing of Electric Motors
Industry 4.0 (I4.0) is accompanied by a variety of technologies which offer great potential for optimizing the manufacturing of electric motors. However, the application of I4.0 technologies in this sector has hardly been examined yet. For determining I4.0 potentials in the electric motor production, a structured approach is required since the variety of sub-processes and production technologies results in a vast number of possible combinations. Therefore, this paper first compares different generic approaches for identifying, selecting and implementing I4.0 use cases. Building on this, a methodical approach is derived in order to tap the numerous I4.0 potentials within the electric motor production. On the one hand, use cases can be derived from current technological opportunities resulting from application examples and best practices in research and industry. On the other hand, concrete problems in critical manufacturing processes can give rise to the application of novel I4.0 solutions. By presenting a comprehensive overview of promising application scenarios, this paper mainly facilitates the identification of I4.0 potentials in the electric motor production from an opportunity-driven perspective. In addition to approaches directly addressing the electric motor production, concepts can be derived from related processes in other application domains. Examples are provided by outlining a selection of the presumably most relevant use cases. The results indicate that especially data-driven approaches, i.e. data analytics and machine learning, offer great potential in electric motor production. As an outlook, I4.0 potentials can also be disclosed from a problem-pull perspective, supplementing the opportunity-push approach of this paper.
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