Manufacturing Analytics for problem-solving processes in production

被引:6
|
作者
Meister, Maximilian [1 ]
Bessle, Julia [1 ]
Cviko, Amir [2 ]
Boeing, Tobias [2 ]
Metternich, Joachim [1 ]
机构
[1] Tech Univ Darmstadt, Inst Prod Management Technol & Machine Tools PTW, Otto Berndt Str 2, D-64287 Darmstadt, Germany
[2] Staufen Qual Engineers GmbH, Blumenstr 5, D-73257 Kongen, Germany
关键词
systematic problem solving process; Manufacturing Analytics; digitalization; Industrie; 4.0;
D O I
10.1016/j.procir.2019.03.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to constantly growing complexity in production complex problems occur more often and problem-solving is of increasing importance. The question arises whether the established methods and tools for problem-solving meet the new requirements. Opportunities emerge through an increased data availability and data analysis can help to support solving complex problems. In order to evaluate resulting possibilities this article examines the importance of Manufacturing Analytics in today's problem-solving processes. Based on an empirical study using interviews to gather experience out of industrial projects it is dealing with fundamentals of modem Manufacturing Analytics and its influence on effective and efficient problem-solving considering statistics, machine learning, data mining and engineering processes. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:1 / 6
页数:6
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