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Towards Learning- and Knowledge-Based Methods of Artificial Intelligence for Short-Term Operative Planning Tasks in Production and Logistics: Research Idea and Framework

机译:迈为基于知识和知识的人工智能方法,用于生产和物流中的短期执行规划任务:研究理念和框架

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摘要

Driven by the increasing digitalization, experts estimate a major change concerning the planning and operation of production systems. The trends indicate a shift from centrally controlled and fixed interlinked production resources to a decentralized production consisting of self-managing cyber-physical systems. This article describe the resulting challenges for the short-term operative production and logistics planning as well as the limitations of current methods. In the further course, the article discusses application potentials of artificial neural networks and fuzzy logic to tackle short-term operative planning tasks in production and logistics. The article concludes with a research framework, which outlines our future steps.
机译:由于数字化的越来越多,专家估计了有关生产系统的规划和运营的重大变革。该趋势表明从集中控制和固定的交互生产资源转移到由自我管理网络物理系统组成的分散生产。本文描述了为短期手术生产和物流规划以及当前方法的限制而挑战。在进一步的过程中,本文讨论了人工神经网络和模糊逻辑的应用势能,以解决生产和物流中的短期操作规划任务。本文与研究框架结束,概述了我们未来的步骤。

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