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Methodology for rapid identification and collection of input data in the simulation of manufacturing systems

机译:在制造系统仿真中快速识别和收集输入数据的方法

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摘要

Computer simulation is a well-established decision support tool in the manufacturing industry. The rapid development and deployment of simulation models however, are inhibited by factors such as inefficient data collection, lengthy model documentation, and poorly planned experimentation. Typically, more than one third of project time is spent on identification, collection, validation, and analysis of input data. Whilst most research work has been focused on statistical techniques for data analysis, less attention has been paid to the development of systematic approaches to input data gathering. This paper presents a methodology for rapid identification and collection of input data in batch manufacturing environments. A functional module library and a reference data model, both developed using the IDEF (Integrated computer aided manufacturing DEFinition) family of constructs, are the core elements of the methodology. The paper also identifies the major causes behind the inefficient collection of data.
机译:计算机仿真是制造业中公认的决策支持工具。但是,仿真模型的快速开发和部署受到诸如数据收集效率低下,模型文档冗长以及实验计划不当等因素的限制。通常,项目时间的三分之一以上用于识别,收集,验证和分析输入数据。尽管大多数研究工作都集中在用于数据分析的统计技术上,但很少关注开发输入数据收集的系统方法。本文提出了一种在批生产环境中快速识别和收集输入数据的方法。均使用IDEF(集成计算机辅助制造DEFinition)构造家族开发的功能模块库和参考数据模型是该方法的核心要素。本文还确定了数据收集效率低下的主要原因。

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