scholarly journals BUSINESS MODEL FRAMEWORK FOR USING REAL-TIME PROCESS DATA FOR DESIGN DECISION MAKING

2011 ◽  
Author(s):  
Matty Janssen ◽  
Paul Stuart
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Business Model ◽  
Environmental Data ◽  
Design Decision ◽  
Time Process ◽  
Time Data ◽  
Process Data ◽  
Model Framework ◽  
Business Decision

In recent years real-time data management systems have become commonplace at pulp and paper mills, and mills seek to use this important resource for improved operation of production facilities as well as for business decision-making. This paper presents a comprehensive and holistic approach to business modeling in which real-time process data, cost data, and environmental data are used in a “bottom-up” manner to exploit their potential for process decision-making. The paper describes a hypothetical case study in which the business model concept is illustrated by application to a process design problem at an integrated newsprint mill.

A Novel Method to Compress Real-Time Process Data

2012 ◽  
Vol 430-432 ◽  
pp. 1298-1301
Author(s):  
Xiao Jian Zheng
Keyword(s):  
Real Time ◽  
Sampling Interval ◽  
Compression Algorithm ◽  
Time Process ◽  
Time Data ◽  
Process Data ◽  
Real Time Data ◽  
Novel Method

Most existing real-time data compressing algorithms are focused on dynamic and inconstancy of the process data, but a basic observation is ignored with some unexpectedness: on condition that sampling interval is not large, difference between amplitudes of real-time process data from two neighboring samples is relatively small, and most of data amplitudes are in the same range. In this paper we propose a compression algorithm based on the observation and experimentally evaluate the proposed approach and demonstrate that our algorithm is promising and efficient.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

The Study of Motor Winding Testing System for Inter-Turn with 30kV

2013 ◽  
Vol 278-280 ◽  
pp. 831-834 ◽  
Author(s):  
Xiao Sun ◽  
Hao Zhou ◽  
Xiang Jiang Lu ◽  
Yong Yang
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Field Test ◽  
Performance Indicators ◽  
Testing System ◽  
Time Data ◽  
Process Data ◽  
Real Time Data ◽  
Long Time ◽  
Factory Testing

This paper designed a motor winding testing system, it can do the dielectric withstand voltage test of inter-turn under 30kV.The system can communicate effectively between PC and machine, by using the PC's powerful capacity of process data and PLC's better stability and the Labview's convenient UI. So the system has real-time data collection, preservation, analysis and other characteristics. This system is able to achieve factory testing and type testing of the motor windings facilitating. Various performance indicators were stable and reliable by field test during a long time.

scholarly journals Bifrost: A Python/C++ Framework for High-Throughput Stream Processing in Astronomy

2017 ◽  
Vol 06 (04) ◽  
pp. 1750007 ◽  
Author(s):  
Miles D. Cranmer ◽  
Benjamin R. Barsdell ◽  
Danny C. Price ◽  
Jayce Dowell ◽  
Hugh Garsden ◽  
...  
Keyword(s):  
Real Time ◽  
High Throughput ◽  
Radio Astronomy ◽  
Scientific Productivity ◽  
Data Transport ◽  
Time Data ◽  
Process Data ◽  
Real Time Processing ◽  
Real Time Data Processing ◽  
High Level

Radio astronomy observatories with high throughput back end instruments require real-time data processing. While computing hardware continues to advance rapidly, development of real-time processing pipelines remains difficult and time-consuming, which can limit scientific productivity. Motivated by this, we have developed Bifrost: an open-source software framework for rapid pipeline development. (a) Bifrost combines a high-level Python interface with highly efficient reconfigurable data transport and a library of computing blocks for CPU and GPU processing. The framework is generalizable, but initially it emphasizes the needs of high-throughput radio astronomy pipelines, such as the ability to process data buffers as if they were continuous streams, the capacity to partition processing into distinct data sequences (e.g. separate observations), and the ability to extract specific intervals from buffered data. Computing blocks in the library are designed for applications such as interferometry, pulsar dedispersion and timing, and transient search pipelines. We describe the design and implementation of the Bifrost framework and demonstrate its use as the backbone in the correlation and beamforming back end of the Long Wavelength Array (LWA) station in the Sevilleta National Wildlife Refuge, NM.

Design and Implementation of Large Computer Room Environment Intelligent Monitoring System Based on Zigbee

2013 ◽  
Vol 397-400 ◽  
pp. 1673-1676 ◽  
Author(s):  
Xing Chen Zhao ◽  
Jin Qiang Li ◽  
Jian Liu ◽  
Quan Shi ◽  
Ling Sun
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Monitoring System ◽  
Environmental Data ◽  
Large Network ◽  
Time Data ◽  
Large Computer ◽  
Switch Control ◽  
Street Lamp ◽  
Intelligent Irrigation

For large network communication equipment are in need of real time computer maintenance and management, the traditional manual management can't meet this need, so this paper designs a set of real-time data acquisition, intelligent alarm and remote control, large computer room environment monitoring system based on Zigbee. The system is composed of terminal monitoring subsystem, control subsystem and management terminal. The terminal monitoring system consists of ZigBee node through the network, and its data acquisition include temperature, humidity and smoke environmental data; MSP430F1611 and Ethernet module monitoring subsystem are responsible for packet analysis, Ethernet connection, and Web intelligent remote switch control when monitoring data reaches a threshold. The system also can be used in street lamp remote intelligent control, intelligent irrigation control system of greenhouse vegetables and so on. Therefore, it has good application value.

Automatic Weather Stations: Tools for Managing and Monitoring Potential Impacts to Coral Reefs

2002 ◽  
Vol 36 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Ray Berkelmans ◽  
Jim C. Hendee ◽  
Paul A. Marshall ◽  
Peter V. Ridd ◽  
Alan R. Orpin ◽  
...  
Keyword(s):  
Environmental Management ◽  
Real Time ◽  
Coastal Development ◽  
Environmental Data ◽  
Limiting Factors ◽  
Data Types ◽  
Time Data ◽  
Effective Manner ◽  
Wide Range ◽  
Weather Stations

With recent technological advances and a reduction in the cost of automatic weather stations and data buoys, the potential exists for significant advancement in science and environmental management using near real-time, high-resolution data to predict biological and/or physical events. However, real-world examples of how this potential wealth of data has been used in environmental management are few and far between. We describe in detail two examples where near real-time data are being used for the benefit of science and management. These include a prediction of coral bleaching events using temperature, light and wind as primary predictor variables, and the management of a coastal development where dynamic discharge quality limits are maintained with the aid of wind data as a proxy for turbidity in receiving waters. We argue that the limiting factors for the use of near real-time environmental data in management is frequently not the availability of the data, but the lack of knowledge of the quantitative relationships between biological/physical processes or events and environmental variables. We advocate renewed research into this area and an integrated approach to the use of a wide range of data types to deal with management issues in an innovative, cost-effective manner.

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