Manufacturing Systems Integration Using Real Time QoS-Aware Middleware

2013 ◽  
Vol 711 ◽  
pp. 629-635 ◽  
Author(s):  
Basem Almadani ◽  
Anas Al-Roubaiey ◽  
Rashad Ahmed
Keyword(s):  
Real Time ◽  
Distribution System ◽  
Manufacturing Systems ◽  
Distributed Applications ◽  
Time Data ◽  
Open Standard ◽  
Middleware Technology ◽  
Automation And Control ◽  
The Cost ◽  
And Control

In recent years, there has been a growth in the amount of data used to improve the production processes. As a result, the cross communication and interaction between components has increased and became a key property of modern production system. To reduce the cost of communication and to increase the efficiency of these systems, middleware technology such as CORBA, COM+, Java RMI, and Web services are being used. Middleware is becoming more and more the essential factor in improving current Manufacturing Process Automation and Control Systems, and their applications have witnessed an increased demand in real time Manufacturing Distributed Applications. In this paper, we propose publish-subscribe middleware architecture based on the Data Distribution System (DDS) open standard. The proposed architecture aims to seamlessly integrate the existing heterogeneous manufacturing systems, such as SCADA system, DCS, PLCs, and databases; and improve the communication and real time data delivery among system components; also, it provides a QoS support layer between the communicating components. Furthermore, the proposed architecture is implemented and evaluated by intensive experiments.

scholarly journals Iot Enabled Pipeline Leakage Detection and Real Time Alert System in Oil and Gas Industry

2020 ◽  
Vol 8 (5) ◽  
pp. 2582-2586
Keyword(s):  
Real Time ◽  
Oil And Gas ◽  
Detection System ◽  
Oil And Gas Industry ◽  
Petroleum Products ◽  
Time Data ◽  
Gas Industry ◽  
Processing Plants ◽  
Automation And Control ◽  
And Control

Automation and control systems are necessary throughout oil & gas industries, to production and processing plants, and distribution and retailing of petroleum products. Pipelines are the efficient mode of transportations of fuels for processing plants over long distances. At present Automation is achieved by using PLC’s that are communicated through SCADA. But it is complex and remote operation is not possible. With the introduction of IoT, the pipeline leak detection system is improved through real-time monitoring of the pipelines. Our Proposed system is designed to detect even small leakage that occurs within the pipeline. The implementation of IoT in oil and gas industries prevents accidents and to make quick decisions based on real-time data

A Data-Driven Simulation-Based Optimisation Approach for Adaptive Scheduling and Control of Dynamic Manufacturing Systems

2016 ◽  
Vol 1140 ◽  
pp. 449-456 ◽  
Author(s):  
Mirko Kück ◽  
Jens Ehm ◽  
Michael Freitag ◽  
Enzo M. Frazzon ◽  
Ricardo Pimentel
Keyword(s):  
Simulation Model ◽  
Real Time ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Shop Floor ◽  
Time Data ◽  
Rush Order ◽  
Real Time Data ◽  
High Flexibility ◽  
And Control

The increasing customisation of products, which leads to higher numbers of product variants with smaller lot sizes, requires a high flexibility of manufacturing systems. These systems are subject to dynamic influences and need increasing effort for the generation of the production schedules and for the control of the processes. This paper presents an approach that addresses these challenges. First, scheduling is done by coupling an optimisation heuristic with a simulation model to handle complex and stochastic manufacturing systems. Second, the simulation model is continuously adapted by real-time data from the shop floor. If, e.g., a machine breakdown or a rush order appears, the simulation model and consequently the scheduling model is updated and the optimisation heuristic adjusts an existing schedule or generates a new one. This approach uses real-time data provided by future cyber-physical systems to integrate scheduling and control and to manage the dynamics of highly flexible manufacturing systems.

scholarly journals A Real-Time, Automatic, and Dynamic Scheduling and Control System for PET Patients Based on Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1104
Author(s):  
Shin-Yan Chiou ◽  
Kun-Ju Lin ◽  
Ya-Xin Dong
Keyword(s):  
Control System ◽  
Real Time ◽  
Human Error ◽  
Dynamic Scheduling ◽  
Wearable Sensors ◽  
Time Data ◽  
Scan Time ◽  
Number Of Patients ◽  
And Control ◽  
Automatic Scheduling

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.

scholarly journals Development of a New KPI for the Economic Quantification of Six Big Losses and Its Implementation in a Cyber Physical System

2020 ◽  
Vol 10 (24) ◽  
pp. 9154
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Royo ◽  
Juan Carlos Sánchez ◽  
Jaime Latapia
Keyword(s):  
Real Time ◽  
Physical System ◽  
Performance Indicator ◽  
Cost Model ◽  
Relevant Information ◽  
Cyber Physical System ◽  
Time Data ◽  
Real Time Data ◽  
Different Dimensions ◽  
The Cost

The purpose of this work is to develop a new Key Performance Indicator (KPI) that can quantify the cost of Six Big Losses developed by Nakajima and implements it in a Cyber Physical System (CPS), achieving a real-time monitorization of the KPI. This paper follows the methodology explained below. A cost model has been used to accurately develop this indicator together with the Six Big Losses description. At the same time, the machine tool has been integrated into a CPS, enhancing the real-time data acquisition, using the Industry 4.0 technologies. Once the KPI has been defined, we have developed the software that can turn these real-time data into relevant information (using Python) through the calculation of our indicator. Finally, we have carried out a case of study showing our new KPI results and comparing them to other indicators related with the Six Big Losses but in different dimensions. As a result, our research quantifies economically the Six Big Losses, enhances the detection of the bigger ones to improve them, and enlightens the importance of paying attention to different dimensions, mainly, the productive, sustainable, and economic at the same time.

Next Generation of Real Time Data Acquisition, Calibration and Control System for the RatCAP Scanner

2007 ◽  
Author(s):  
Sachin S Junnarkar ◽  
Jack Fried ◽  
Sudeepti Southekal ◽  
Jean-Francois Pratte ◽  
Paul O'Connor ◽  
...  
Keyword(s):  
Control System ◽  
Data Acquisition ◽  
Real Time ◽  
Next Generation ◽  
Time Data ◽  
Real Time Data ◽  
And Control

Sectional Data Acquisition and Control System for Solar Street Lamps Based on Internet of Things

2013 ◽  
Vol 773 ◽  
pp. 148-153 ◽  
Author(s):  
Juan Zhou ◽  
Bing Yan Chen ◽  
Meng Ni Zhang ◽  
Ying Ying Tang
Keyword(s):  
Control System ◽  
Internet Of Things ◽  
Data Acquisition ◽  
Real Time ◽  
Network Flow ◽  
Short Interval ◽  
Management Problem ◽  
Time Data ◽  
Control Centre ◽  
And Control

Aiming at the management problem of real-time data created while intelligent solar street lamps working, sectional data acquisition and control system based on internet of things is introduced in the paper. Communication protocol with unified form and flexible function is designed in the system, and communication address is composed of sectional address and subsection address. Three-level data structure is built in the polling algorithm to trace real-time state of lamps and to detect malfunction in time, which is suitable for sectional lamps management characteristics. The system reflects necessary statistic data and exception information to remote control centre through GPRS to short interval expend on transmission and procession and save network flow and system energy. The result shows the system brings improved management affection and accords with the idea of energy-saving and environmental protection.

scholarly journals DC Microgrid Utilizing Artificial Intelligence and Phasor Measurement Unit Assisted Inverter

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6086
Author(s):  
Raziq Yaqub ◽  
Mohamed Ali ◽  
Hassan Ali
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Distribution System ◽  
Reference Signal ◽  
Phasor Measurement Unit ◽  
Measurement Unit ◽  
Time Data ◽  
Dc Microgrid ◽  
Utility Company ◽  
Phasor Measurement

Community microgrids are set to change the landscape of future energy markets. The technology is being deployed in many cities around the globe. However, a wide-scale deployment faces three major issues: initial synchronization of microgrids with the utility grids, slip management during its operation, and mitigation of distortions produced by the inverter. This paper proposes a Phasor Measurement Unit (PMU) Assisted Inverter (PAI) that addresses these three issues in a single solution. The proposed PAI continually receives real-time data from a Phasor Measurement Unit installed in the distribution system of a utility company and keeps constructing a real-time reference signal for the inverter. To validate the concept, a unique intelligent DC microgrid architecture that employs the proposed Phasor Measurement Unit (PMU) Assisted Inverter (PAI) is also presented, alongside the cloud-based Artificial Intelligence (AI), which harnesses energy from community shared resources, such as batteries and the community’s rooftop solar resources. The results show that the proposed system produces quality output and is 98.5% efficient.

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