South Belut Data Acquisition: Leveraging Real Time Production Data from IWS Wells for Reservoir Characterisation

2018 ◽  
Author(s):  
Adam Beck
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Production Data ◽  
Time Production

Determination of Water Producing Zones While Under-balanced Drilling Horizontal Wells - Integration of Sigma Log and Real-Time Production Data

2007 ◽  
Author(s):  
Philippe Jean Gauthier ◽  
Hassan Hussain ◽  
John Bowling ◽  
John Ernest Edwards ◽  
Bernd Herold
Keyword(s):  
Real Time ◽  
Horizontal Wells ◽  
Production Data ◽  
Time Production

Enabling Numerical Simulation and Real-Time Production Data to Monitor Waterflooding Indicators

2013 ◽  
Author(s):  
Dhruv Vanish ◽  
Dayanara Betancourt ◽  
Shikin MdAdnan ◽  
Feng Wang ◽  
Alvin Stan Cullick ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Real Time ◽  
Production Data ◽  
Time Production

Proactive Optimization of Oil Recovery in Multilateral Wells Using Real Time Production Data

2009 ◽  
Author(s):  
Zeid Alghareeb ◽  
Roland N. Horne ◽  
Bevan Bun Wo Yuen ◽  
Shamsuddin H. Shenawi
Keyword(s):  
Real Time ◽  
Oil Recovery ◽  
Production Data ◽  
Time Production

RFID-Enabled Real-Time Production Tracking System for PCB Assembly Industry

2011 ◽  
Vol 80-81 ◽  
pp. 1330-1334 ◽  
Author(s):  
Gong Zhang ◽  
Jie Zhang ◽  
Shi Yong Tian
Keyword(s):  
Real Time ◽  
Production Management ◽  
Tracking System ◽  
Production Data ◽  
Time Data ◽  
Time Production ◽  
Pcb Assembly ◽  
Real Time Data ◽  
Information Tracking ◽  
The Right

There are many varieties of materials and suppliers for the PCB assembly process; meanwhile, process modifications as well as order changings happen frequently during production. The PCB assembly industry is suffering uncertainty and unknowingness due to the lack of timely, accurate, and consistent production data. Therefore, real-time production information tracking plays an important role for the PCB assembly industry, which provides the right information to the right person at right time to support the decision making and optimize the production management. This paper applies RFID technology to capture the production data and process production information for PCB assembly enterprises. In a PCB assembly line, machines and materials are equipped with RFID device such as RFID readers and tags to build the real-time data collecting environment. A number of production information processing methods are proposed to extract the production tracking information such as progress, WIP (Work-in-progress) inventory from the mass real-time data through data filtering and selection. Finally, a case study is given to demonstrate the developed methodologies.

scholarly journals Automatic Multiple Sensor Data Acquisition System in a Real-time Production Environment

Procedia CIRP ◽  
2015 ◽  
Vol 33 ◽  
pp. 215-220 ◽  
Author(s):  
Jonathan Downey ◽  
Sebastian Bombiński ◽  
Mirosław Nejman ◽  
Krzysztof Jemielniak
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Sensor Data ◽  
Production Environment ◽  
Time Production ◽  
Multiple Sensor ◽  
Sensor Data Acquisition

scholarly journals Intelligent IoT systems for civil infrastructure health monitoring: a research roadmap

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
E. Bertino ◽  
M. R. Jahanshahi ◽  
A. Singla ◽  
R.-T. Wu
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Original Data ◽  
Local Analysis ◽  
Civil Infrastructure ◽  
Time Requirements ◽  
Iot Devices ◽  
Learning Reinforcement ◽  
The Times ◽  
Acquisition Processes

AbstractThis paper addresses the problem of efficient and effective data collection and analytics for applications such as civil infrastructure monitoring and emergency management. Such problem requires the development of techniques by which data acquisition devices, such as IoT devices, can: (a) perform local analysis of collected data; and (b) based on the results of such analysis, autonomously decide further data acquisition. The ability to perform local analysis is critical in order to reduce the transmission costs and latency as the results of an analysis are usually smaller in size than the original data. As an example, in case of strict real-time requirements, the analysis results can be transmitted in real-time, whereas the actual collected data can be uploaded later on. The ability to autonomously decide about further data acquisition enhances scalability and reduces the need of real-time human involvement in data acquisition processes, especially in contexts with critical real-time requirements. The paper focuses on deep neural networks and discusses techniques for supporting transfer learning and pruning, so to reduce the times for training the networks and the size of the networks for deployment at IoT devices. We also discuss approaches based on machine learning reinforcement techniques enhancing the autonomy of IoT devices.

scholarly journals Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4836
Author(s):  
Liping Zhang ◽  
Yifan Hu ◽  
Qiuhua Tang ◽  
Jie Li ◽  
Zhixiong Li
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Real Time ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Data Driven ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Production Data ◽  
Online Decision Making

In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

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.

A real time, wireless and low cost data acquisition system for residential PV modules

2020 ◽  
Author(s):  
Cheyma BARKA ◽  
Hanen MESSAOUDI-ABID ◽  
Houda BEN ATTIA SETTHOM ◽  
Afef BENNANI-BEN ABDELGHANI ◽  
Ilhem SLAMA-BELKHODJA ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Low Cost ◽  
Data Acquisition System ◽  
Cost Data ◽  
Acquisition System ◽  
Pv Modules
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