AI for in-line vehicle sequence controlling: development and evaluation of an adaptive machine learning artifact to predict sequence deviations in a mixed-model production line

IF 2.5 3区工程技术 Q2 ENGINEERING, INDUSTRIAL

Flexible Services and Manufacturing Journal Pub Date : 2021-08-15 DOI:10.1007/s10696-021-09430-x

Maximilian Stauder, Niklas Kühl

引用次数: 6

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用于在线车辆序列控制的人工智能:自适应机器学习工件的开发和评估，以预测混合模型生产线中的序列偏差

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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来源期刊

Flexible Services and Manufacturing Journal ENGINEERING, MANUFACTURING-OPERATIONS RESEARCH & MANAGEMENT SCIENCE

CiteScore

5.60

自引率

7.40%

发文量

审稿时长

>12 weeks

期刊介绍： The mission of the Flexible Services and Manufacturing Journal, formerly known as the International Journal of Flexible Manufacturing Systems, is to publish original, high-quality research papers in the field of services and manufacturing management. All aspects in this field including the interface between engineering and management, the design and analysis of service and manufacturing systems as well as operational planning and decision support are covered. The journal seeks papers that have a clear focus on the applicability in the real business world including all kinds of services and manufacturing industries, e.g. in logistics, transportation, health care, manufacturing-based services, production planning and control, and supply chain management. Flexibility should be understood in its widest sense as a system’s ability to respond to changes in the environment through improved decision making and business development procedures and enabling IT solutions.