制造系统模拟中快速识别和收集输入数据的方法学

T. Perera, K. Liyanage
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引用次数: 109

摘要

计算机仿真在制造业中是一种成熟的决策支持工具。然而,仿真模型的快速开发和部署受到诸如低效的数据收集、冗长的模型文档和计划不良的实验等因素的抑制。通常,超过三分之一的项目时间花在识别、收集、验证和分析输入数据上。虽然大多数研究工作都集中在数据分析的统计技术上,但很少注意发展系统的输入数据收集方法。本文提出了一种在批量生产环境中快速识别和收集输入数据的方法。功能模块库和参考数据模型是该方法的核心元素,它们都是使用IDEF(集成计算机辅助制造定义)构造家族开发的。本文还指出了数据收集效率低下背后的主要原因。
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Methodology for rapid identification and collection of input data in the simulation of manufacturing systems

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.

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