An integrated holistic model of a complex process
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- 作者：Heeyoung Kim ; Sungil Kim ; Jianxin Deng…
- 关键词：Combining data ; Initial modeling ; Model integration ; Multiple sub ; experiments
- 刊名：The International Journal of Advanced Manufacturing Technology
- 出版年：2017
- 出版时间：March 2017
- 年：2017
- 卷：89
- 期：1-4
- 页码：1137-1147
- 全文大小：
- 刊物类别：Engineering
- 刊物主题：Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design;
- 出版者：Springer London
- ISSN：1433-3015
- 卷排序：89
文摘
Conducting experiments to understand and model a complex process or system is usually costly and time-consuming due to multistages, multivariables, and multidisciplinary issues involved in the complex process. To reduce the complexity, for a single experiment, experimenters often fix some variables and investigate the effects of a smaller subset of variables. If then, it is possible to build individual models for each subset of variables, but this only allows partial understanding of the whole process. In this paper, we propose a method for building a holistic model of a complex process using multiple partial models that are learned from multiple sub-experiments that focus on different variables or the same variables but with different variable ranges. Using the proposed holistic model, it should be possible to provide an initial understanding of the complex process involving all variables. The effectiveness of the proposed method is demonstrated using a real example from a buckypaper process.