Digital twin for the single and small batch production

适用于单件和小批量生产的数字孪生

基本信息

批准号：
406411721
负责人：
Professor Dr.-Ing. Günther Schuh
金额：
--
依托单位：
Werkzeugmaschinenlabor - WZL
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2018
资助国家：
德国
起止时间：
2017-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/406411721?language=en
关键词：
Digital twin single small batch

项目摘要

The goal of this research project is to investigate the dependencies among the captured data in manufacturing processes in order to develop a production twin model. Both, directly and indirectly, interdependent data is examined for cause-effect relationships, and thus form the basis for an efficient and effective improvement of manufacturing processes. The use of data further supports to simulate production processes and to shorten the time-to-market significantly. An evaluation and use of data allows the single and small series production to optimize the planning whereby lead times can be reduced. The optimization of individual sections of the production is not effective. An increase of the efficiency can only be achieved by optimizing the overall production system. However, this requires an understanding of the entire production process and dependencies of their individual sub-processes. An understanding and accurate representation of the dependency of processes and parameters allow then to predict certain events and finally help to interfere in case of negative events. The requirements for a proactive intervention in the process is the understanding and documentation of cause-effect relationships of individual processes or sub-processes, which can be attained through the understanding of data dependencies. The identified data and cause-effect relationships between these data are combined finally to a digital production twin model. The results to be achieved can be divided into seven sub-goals: a) Creation of a generic catalog of all generated and relevant data in single and small series production companies b) Creation of a generic catalog of all stored data in single and small series production companies c) Development of dependency patterns between data structures d) Portrait of the dependencies in data structures in the form of a multidimensional matrix e) Identification of positive and negative data dependencies f) Identification of dependencies in the form of causeeffect relationships of different data structures g) Integration of the data and the cause-effect relationships to a digital production twin model.

该研究项目的目的是研究制造过程中捕获的数据之间的依赖性，以开发生产双胞胎模型。直接和间接地检查了相互依存的数据是否有因果关系，因此构成了有效有效改进制造过程的基础。数据的使用进一步支持以模拟生产过程并大大缩短市场时间。数据的评估和使用允许单个和小型系列生产优化可以减少交货时间的计划。生产各个部分的优化无效。效率的提高只能通过优化整体生产系统来实现。但是，这需要了解其各个子过程的整个生产过程和依赖性。对过程和参数的依赖性的理解和准确表示可以预测某些事件，并最终有助于干扰负面事件。在该过程中积极干预的要求是对单个过程或子过程的因果关系的理解和记录，这可以通过理解数据依赖性来实现。这些数据之间已确定的数据和原因效应关系最终结合到数字生产双胞胎模型。可以将要实现的结果分为七个子目标：a）创建单个和小型系列生产公司中所有生成和相关数据的通用目录b）创建单个和小型系列生产公司中所有存储数据的一般目录c）在数据结构之间的依赖性依赖性和依赖数据的依赖性e依赖的依赖性e依赖的依赖性ixcix and Indie firix的依赖性的依赖性的依赖性的依赖性d）d）以不同数据结构的Causeefect关系形式识别依赖关系g）数据的整合以及与数字生产双胞胎模型的原因效应关系。