Automation using Plc and IIoT Monitoring in Jaggery Preparation
G.Jayanthi1, S.Aaradhika2, S.Swathy3, N.Mathumitha4

1G.Jayanthi, Department Of Instrumentation and Control Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India.
2S. Aaradhika, Department Of Instrumentation and Control Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India.
3S. Swathy, Department Of Instrumentation and Control Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India.
4N. Mathumitha, Department Of Instrumentation and Control Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India.

Manuscript received on October 16, 2019. | Revised Manuscript received on 24 October, 2019. | Manuscript published on November 10, 2019. | PP: 5227-5230 | Volume-9 Issue-1, November 2019. | Retrieval Number: A9236119119/2019©BEIESP | DOI: 10.35940/ijitee.A9236.119119
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Abstract: Jaggery is a natural sugar which a sweetening agent and is also called as gur or panela. It is first made into a semisolid paste by evaporating the sugarcane juice. The aim of this paper is to develop an automated process for Jaggery preparation using PLC and monitored by IIOT (Industrial Internet Of Things). The process consists of pushbuttons, Temperature sensor (LM35), Level sensor (Ultrasonic level transmitter), IR sensor as input devices which are interfaced with the Siemens PLC(CPU314-2C). The PLC controls the following output devices such as crusher motor, conveyor motor, scum motor and valves (pneumatic actuator control valve).The process parameters are uploaded into the cloud for monitoring using IIOT. The trend graphs are generated using MindSphere software (MindConnect Nano). The system also provides fault detection through alert messages and e-mails. The protocol used for IIOT is Transmission Control Protocol (TCP). All the five stages such as crushing, filtering, heating, cooling and molding of the Jaggery preparation process are automated. Thus, a hygienic and fully automatic PLC based Jaggery production system with fault detection capability is developed through this project.
Keywords: PLC, IIoT, MindSphere, MindConnect Nano, Trend plot, Fault detection, TCP.
Scope of the Article: Industrial Internet of Things (IIoT)