Pattern Recurring in Three-Dimensional Graph Based on Data Mining

2006 ◽  
pp. 919-926
Author(s):  
Yanbing Liu ◽  
Menghao Wang
Keyword(s):  
Data Mining ◽  
Three Dimensional ◽  
Dimensional Graph

Motion Analysis and Simulation of Complex Curved Surface WEDM System

2008 ◽  
Vol 392-394 ◽  
pp. 151-155
Author(s):  
Tong Wang ◽  
K. Jiang ◽  
Shu Qiang Xie ◽  
Shuang Shuang Hao
Keyword(s):  
Electrical Discharge Machining ◽  
Three Dimensional ◽  
Simulation Method ◽  
Curved Surface ◽  
Polar Coordinates ◽  
Curved Surfaces ◽  
Machining Quality ◽  
Motion Parameters ◽  
Dimensional Graph ◽  
Analysis Of Motion

In this paper, the characteristics and general laws of cutting complex curved surface by wire electrical discharge machining (WEDM) system are studied. Based on analysis of motion parameters the universal mathematical model of polar coordinates is derived. Moreover, the simulation of WEDM system is introduced, which is carried out by using language Visual C++ and the three dimensional graph software OpenGL.This simulation method is helpful in improving machining quality and productivity of complex curved surfaces, and is fundation for establishing CAD/CAPP/CAM technology in WEDM.

A framework for big data driven process analysis and optimization for additive manufacturing

2019 ◽  
Vol 25 (2) ◽  
pp. 308-321 ◽  
Author(s):  
Arfan Majeed ◽  
Jingxiang Lv ◽  
Tao Peng
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Additive Manufacturing ◽  
Production Efficiency ◽  
Process Analysis ◽  
Three Dimensional ◽  
Big Data Analytics ◽  
Production Performance ◽  
Content Type ◽  
Processing And Storage

Purpose This paper aims to present an overall framework of big data-based analytics to optimize the production performance of additive manufacturing (AM) process. Design/methodology/approach Four components, namely, big data application, big data sensing and acquisition, big data processing and storage, model establishing, data mining and process optimization were presented to comprise the framework. Key technologies including the big data acquisition and integration, big data mining and knowledge sharing mechanism were developed for the big data analytics for AM. Findings The presented framework was demonstrated by an application scenario from a company of three-dimensional printing solutions. The results show that the proposed framework benefited customers, manufacturers, environment and even all aspects of manufacturing phase. Research limitations/implications This study only proposed a framework, and did not include the realization of the algorithm for data analysis, such as association, classification and clustering. Practical implications The proposed framework can be used to optimize the quality, energy consumption and production efficiency of the AM process. Originality/value This paper introduces the concept of big data in the field of AM. The proposed framework can be used to make better decisions based on the big data during manufacturing process.

Information Visualization with Text Data Mining for Knowledge Discovery Tools in Bioinformatics

2005 ◽  
Vol 277-279 ◽  
pp. 259-265
Author(s):  
Jin Ah Park ◽  
Chang Su Lee ◽  
Jong C. Park
Keyword(s):  
Data Mining ◽  
3D Visualization ◽  
Three Dimensional ◽  
Mitogen Activated Protein Kinase ◽  
Text Data ◽  
Text Data Mining ◽  
Visualization System ◽  
Source Data ◽  
Mitogen Activated Protein ◽  
Available Information

An abundant amount of information is produced in the digital domain, and an effective information extraction (IE) system is required to surf through this sea of information. In this paper, we show that an interactive visualization system works effectively to complement an IE system. In particular, three-dimensional (3D) visualization can turn a data-centric system into a user-centric one by facilitating the human visual system as a powerful pattern recognizer to become a part of the IE cycle. Because information as data is multidimensional in nature, 2D visualization has been the preferred mode. However, we argue that the extra dimension available for us in a 3D mode provides a valuable space where we can pack an orthogonal aspect of the available information. As for candidates of this orthogonal information, we have considered the following two aspects: 1) abstraction of the unstructured source data, and 2) the history line of the discovery process. We have applied our proposal to text data mining in bioinformatics. Through case studies of data mining for molecular interaction in the yeast and mitogen-activated protein kinase pathways, we demonstrate the possibility of interpreting the extracted results with a 3D visualization system.

Finding patterns in three-dimensional graphs: algorithms and applications to scientific data mining

2002 ◽  
Vol 14 (4) ◽  
pp. 731-749 ◽  
Author(s):  
Xiong Wang ◽  
J.T.L. Wang ◽  
D. Shasha ◽  
B.A. Shapiro ◽  
I. Rigoutsos ◽  
...  
Keyword(s):  
Data Mining ◽  
Three Dimensional ◽  
Scientific Data ◽  
Scientific Data Mining
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