Ali Moallim

Bio: Ali Moallim is an academic researcher from Kumoh National Institute of Technology. The author has contributed to research in topics: Automation & Arduino. The author has an hindex of 1, co-authored 1 publications receiving 8 citations.

Wireless control and monitoring using Programmable Logic Controller (PLC)

Abstract: In recent years, in response to market demands, many features and functions are introduced to Programmable Logic Controllers (PLC). Today's PLCs are already benefiting from various new technologies, and built-in wireless is among evolving features that have not been widely adopted yet. This paper discusses the potential of utilizing ZigBee protocol for addressing wireless PLC current limitations through the design and implementation of a real-time wireless control and monitoring system. A Zigbee based wireless unit is implemented employing Arduino. The Arduino device provides network control flexibility and easy system reconfiguration. The evaluation results show the effectiveness of the proposed design and its feasibility in real-time wireless control and monitoring home and industrial application.

Design and implementation of a programmable logic controller using PIC18F4580

Abstract: Use of electricity in industry opened a new age which is dominated by industrial automation. In the beginning, automation systems were based on electro-mechanical systems consisting of relays and contactors. Developments in semiconductor technology inevitably transformed the existing structure and cause electronic-controlled Programmable Logic Controller (PLC) to prevail in the automation systems. PLCs consist of a microcontroller/microprocessor, relay or transistor for switching, isolating equipment such as opto-couplers and voltage converter/inverters. Industrial PLCs are quite expensive devices. In this study, design and implementation of a low-cost PLC using PIC18F4580 microcontroller are realized. Special software including a graphical user-interface is developed for programming the PLC and transferring code data to the device. Both ladder diagram and word instructions can be used for programming the PLC.

A Low-Cost and Scaled Automation System for Education in Industrial Automation

Abstract: Modern automation systems consist of assemblies of mechanical and electrical components commanded through digital controllers. The physical implementation of automation systems in education is difficult due to the current costs of industrial automation hardware. This constrains automation courses to only theoretical and/or virtual activities. This paper proposes the implementation of a scaled automation system through the mixing of industrial and prototype hardware. The defined low-cost architecture allows students to practically experience fundamental concepts of industrial automation as PLC code design and verification, SCADA development, and system remote control.

A smart PLC-SCADA framework for monitoring petroleum products terminals in industry 4.0 via machine learning

Abstract: The paper introduces a Programmable Logic Controller (PLC) / Human Machine Interface (HMI) system incorporated along with machine learning (ML) classifiers. Although some other studies have incorporated ML techniques to predict and control petroleum product terminals in terms of concentration, the proposed framework incorporates Add On Instruction (AOI) programming, PLC, and ML methods to automatically monitor petroleum products terminals. The framework adds an AOI in programming to achieve maximum usage of processor capabilities. Moreover, it uses AOI for programming in cooperation with the ladder diagram (LD). This leads to simplifying the LD graphical programming language, reducing the time of scanning, and making facilitate troubleshooting. The AOI is merged with ML to automate tank level detection and maintain good operational conditions and consequently protect these expensive essential assets. The introduced framework consists of three stages. The first stage is the PLC programming phase where the PLC is created using Add-On instructions. Next, HMI graphic displays are drawn and linked to the PLC tags in the following stage. During the third stage, the actual process readings are applied to the system based on ML algorithms to test its functionality. The proposed system results indicates a reduction in the LD number, highest program size, and maximum time of scanning. The results indicate that the AOI can help to trace the program more easily in fault situations. Besides, additional program instructions could reduce processor memory, system construction costs, and upgrade projects.

IoT Based Industrial Monitoring System

Abstract: The Industrial Internet of things or IIoT has gained recognition due to the advancement it has made in communication technology. Industrial IoT is an application of IoT that enables control of industries over the Internet using smart devices and sensors. The two main entity which ensures effectiveness in any field is monitoring and control. Keeping a view on this aspect, we have designed a low-cost, low-power Wi-Fi based industrial monitoring system that controls and monitors the remote manufacturing plants and industries using a web application. In this model an Arduino Mega which is the main micro-controller is connected with a Wi-Fi module for internet connectivity, a barometer sensor for temperature and pressure, a humidity sensor for sensing the humidity and a gas sensor which detects the smoke and harmful gases. These components are utilized to build a monitoring system. Apart from these components several other sensors are used to keep a check on the temperature, gas leakage, pressure, humidity, etc. in the work environment to ensure the workers safety. In case of any incident this monitoring system warns the workers by an alarm and sends information to the registered user via Blynk App. The chief purpose of this research is to sum up the significant role of IoT in monitoring industries.