Intelligent Processing of Materials

MRS Bulletin ◽  
1988 ◽  
Vol 13 (4) ◽  
pp. 17-20
Author(s):  
H. Thomas Yolken

Advanced materials can provide specialized properties, or combinations of properties, that cannot be obtained in conventional materials. However, advanced materials generally require unusual processing operations in order to achieve their unique microstructures and the resulting greatly improved properties. These materials also tend to be expensive because of the high value added by unusual processing operations that may be labor intensive. Because the relationships among the processing parameters, microstructure, and resulting material properties and performance are not fully understood, and because the microstructure is difficult to control, reproducibility in these materials is often unsatisfactory. A very promising direction toward overcoming these difficulties involves intelligent processing of materials, a computer-based approach to automatically controlling the evolution of microstructure during processing.In a conventional automated materials processing system, automation involves utilizing sensors to monitor process variables such as temperature and pressure. Data from these sensors are compared with preset values automatically in order to maintain these values with control devices. Nevertheless, the microstructure and properties often experience significant variations. The variations are detected after the fact either by destructive analysis in a quality control laboratory or by nondestructive evaluation (NDE) at the end of the manufacturing process.In contrast, an intelligent processing system utilizes a new class of NDE sensors to characterize the microstructure of the material in real time. Moreover, the real-time data plus data from conventional process variable sensors are transmitted to a computerized decision maker.

2014 ◽  
Vol 571-572 ◽  
pp. 497-501 ◽  
Author(s):  
Qi Lv ◽  
Wei Xie

Real-time log analysis on large scale data is important for applications. Specifically, real-time refers to UI latency within 100ms. Therefore, techniques which efficiently support real-time analysis over large log data sets are desired. MongoDB provides well query performance, aggregation frameworks, and distributed architecture which is suitable for real-time data query and massive log analysis. In this paper, a novel implementation approach for an event driven file log analyzer is presented, and performance comparison of query, scan and aggregation operations over MongoDB, HBase and MySQL is analyzed. Our experimental results show that HBase performs best balanced in all operations, while MongoDB provides less than 10ms query speed in some operations which is most suitable for real-time applications.


2014 ◽  
Vol 1061-1062 ◽  
pp. 1186-1189
Author(s):  
Ming Zhe Wei ◽  
Wan Wei Tang

With the rapid development of aerial UAV (Unmanned Aerial Vehicle), the design of real-time data acquisition and transmission system for the video signal has a new applied field. It is different from traditional video acquisition and processing system, aerial video signal has the problems of screen jitter and spatial interference. The processing algorithm of aerial UAV airborne video signal is put forward in the paper, and the platform of high speed procession is constructed based on chip TMS320DM642, and get a good effect.


2013 ◽  
Vol 278-280 ◽  
pp. 749-752 ◽  
Author(s):  
Peng Wang ◽  
Chi Zhong Wang ◽  
Ze Sen Liu ◽  
Xu Han ◽  
Cao Wang Si ◽  
...  

In this paper, the real-time defects inspection was implemented via use of paralleled structure and high-speed operation of FPGA. The hardware circuit based on FPGA was established. According to signal characteristics of polymeric film defects, the preprocessing scheme of defect images based on FPGA was designed. The defect data were packed according to the defined format. Data processed were transferred to PC through USB2.0 real-timely to reconstruct defect microscopic images. The quantity of transferred data was decreased tremendously by this method. The inspecting speed was greatly improved.


1975 ◽  
Vol 23 (4) ◽  
pp. 271-279
Author(s):  
YOSHIAKI KATO ◽  
YOSHIO TAJIMA ◽  
HAJIME HAYAKAWA ◽  
ATSUSHI SHIBATA ◽  
KOUJI NISHIWAKI

2021 ◽  
pp. 147-156
Author(s):  
Fabiana Fournier ◽  
Inna Skarbovsky

AbstractTo remain competitive, organizations are increasingly taking advantage of the high volumes of data produced in real time for actionable insights and operational decision-making. In this chapter, we present basic concepts in real-time analytics, their importance in today’s organizations, and their applicability to the bioeconomy domains investigated in the DataBio project. We begin by introducing key terminology for event processing, and motivation for the growing use of event processing systems, followed by a market analysis synopsis. Thereafter, we provide a high-level overview of event processing system architectures, with its main characteristics and components, followed by a survey of some of the most prominent commercial and open source tools. We then describe how we applied this technology in two of the DataBio project domains: agriculture and fishery. The devised generic pipeline for IoT data real-time processing and decision-making was successfully applied to three pilots in the project from the agriculture and fishery domains. This event processing pipeline can be generalized to any use case in which data is collected from IoT sensors and analyzed in real-time to provide real-time alerts for operational decision-making.


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