scholarly journals Implementation of flow control over WirelessHART sensor network using WirelessHART adaptors

2019 ◽  
Vol 15 (2) ◽  
pp. 910
Author(s):  
Sabo Miya Hassan ◽  
Kishore Bingi ◽  
Rosdiazli Ibrahim ◽  
Lim Jin Chein ◽  
ThasarathaRao Supramaniam
Keyword(s):  
Wireless Networks ◽  
Process Control ◽  
Flow Control ◽  
Sensor Network ◽  
Process Automation ◽  
Industrial Automation ◽  
Flow Process ◽  
Wireless Control ◽  
Wireless Standards ◽  
Real Plant

<p>Despite the advantages of the industrial wireless standards such as WirelessHART, ISA100.11a and Wireless Networks for Industrial Automation-Process Automation (WIA-PA), their application still faces a lot of challenges especially when it comes to interfacing with the real plant. This is due to lack of adequate infrastructures such as interfacing circuitry to establish communication between the WirelessHART nodes and the actuators and sensors. Therefore, this paper presents the application of locally developed WirelessHART adaptors for flow process control. The adaptors serve as an interface between the WirelessHART network and the sensor and actuator of the plant. Experimental results of the controllers compared showed that wireless control is possible through the use of the adaptors.</p>

Open Process Automation: A standards-based, open, secure, interoperable process control architecture

2022 ◽  
Vol 121 ◽  
pp. 105034
Author(s):  
R. Donald Bartusiak ◽  
Stephen Bitar ◽  
David L. DeBari ◽  
Bradley G. Houk ◽  
Dennis Stevens ◽  
...  
Keyword(s):  
Process Control ◽  
Control Architecture ◽  
Process Automation ◽  
Open Process

Wireless Control for Pointolite in Light-Pen CMMs

2014 ◽  
Vol 602-605 ◽  
pp. 2217-2220 ◽  
Author(s):  
Rui Zhang ◽  
Shu Gui Liu ◽  
Huai Yu Wang
Keyword(s):  
Wireless Networks ◽  
Control System ◽  
Wireless Communication ◽  
Success Rate ◽  
Experimental Result ◽  
Error Reporting ◽  
Wireless Control ◽  
Light Pen

A wireless control system for pointolite on the light pen based on TMS320DM642 and CC2530 is introduced in this paper, in order to solve the problem that only pointolite's switch values could be controlled on the light pen in light-pen CMMs, but not lightening time values and brightness values. Through wireless networks of Zigbee, not only pointolite could be switched on or off separately, but also lightening time values and brightness values could be changed by TMS320DM642. Protocols of wired and wireless communication, multipoint answer and error reporting are also given, to improve anti-jamming capability of the system. The experimental result demonstrates that the control success rate could reach 96%, as the wireless modules of TMS320DM642 and the light pen within 8m. So the developed system has high anti-interference capability and could meet expected requirements.

A Supervised Machine Learning Approach for Intelligent Process Automation in Container Logistics

2020 ◽  
Vol 20 (3) ◽  
Author(s):  
David Bricher ◽  
Andreas Müller
Keyword(s):  
Process Control ◽  
Production Scheduling ◽  
Deep Neural Networks ◽  
Supervised Machine Learning ◽  
Data Sets ◽  
Process Automation ◽  
Container Logistics ◽  
Machine Operators ◽  
Machine Learning Approach ◽  
Intelligent Process

Abstract Process control in manufacturing industries usually lacks flexibility and adaptability. The process planning is traditionally pursued within the production scheduling and then remains unchanged until a major overhaul is necessary. Consequently, no process knowledge acquired by the machine operators is used to adapt, and thus improve, the process control. In this paper, a fully automated process control solution for container logistics is proposed, which is based on deep neural networks and has been trained from process steering decisions made by employees. Further, a fully automated framework for the labeling of container images is introduced, making use of inherent properties of the logistic process. This allows to automatically generate data sets without the need for manual labeling by an operator.

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