Modeling and optimization of manufacturing process performance using Modelica graphical representation and process analytics formalism
被引:0
作者:
G. Shao
论文数: 0引用数: 0
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机构:National Institute of Standards and Technology,System Integration Division, Engineering Laboratory
G. Shao
A. Brodsky
论文数: 0引用数: 0
h-index: 0
机构:National Institute of Standards and Technology,System Integration Division, Engineering Laboratory
A. Brodsky
R. Miller
论文数: 0引用数: 0
h-index: 0
机构:National Institute of Standards and Technology,System Integration Division, Engineering Laboratory
R. Miller
机构:
[1] National Institute of Standards and Technology,System Integration Division, Engineering Laboratory
[2] George Mason University,Department of Computer Science
[3] University of Texas at Dallas,Department of Computer Science
来源:
Journal of Intelligent Manufacturing
|
2018年
/
29卷
关键词:
Optimization;
Manufacturing process;
Process analytics;
Graphical user interface;
D O I:
暂无
中图分类号:
学科分类号:
摘要:
This paper concerns the development of a design methodology and its demonstration through a prototype system for performance modeling and optimization of manufacturing processes. The design methodology uses a Modelica simulation tool serving as the graphical user interface for manufacturing domain users such as process engineers to formulate their problems. The Process Analytics Formalism, developed at the National Institute of Standards and Technology, serves as a bridge between the Modelica classes and a commercial optimization solver. The prototype system includes (1) manufacturing model components’ libraries created by using Modelica and the Process Analytics Formalism, and (2) a translator of the Modelica classes to Process Analytics Formalism, which are then compiled to mathematical programming models and solved using an optimization solver. This paper provides an experiment toward the goal of enabling manufacturing users to intuitively formulate process performance models, solve problems using optimization-based methods, and automatically get actionable recommendations.