Simulink Model for Adaptive Speed Control of Lathe Machine for Installing Vfd Using Matlab
Santosh Gangwar1, P. Sudhakar. Rao2, Ajay Kumar3

1Km Santosh Gangwar, Department of M.E. Scholar in National Institute of Technical Teachers Training and Research, Bhopal, Madhya Pradesh
2Dr. P. Sudhakar Rao, Assistant Professor Department of Mechanical Engineering, NITTTR Chandigarh.
3Ajay Kumar, Director Enovative lab, NITTTR Chandigarh. He Completed his M.E. from NITTTR Chandigarh in 2017.
Manuscript received on 25 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 579-583 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7797078919/19©BEIESP | DOI: 10.35940/ijitee.I7797.078919

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Abstract: In modern scenario it is necessary to update the existing machine according to the latest technology or as per the demand/requirement and conservation of energy is also an important task. The demand of energy increases day by day. As we know that the conventional lathe machine has an important role in every industry, workshop, and colleges in different operation required for the research work or manufacturing in various parts. But some time it is very difficult to handle lathe machine specially in handling/controlling the speed. So in this project we control the speed of lathe machine by using Variable Frequency Derive (VFD) with SIMULINK model generated in MATLAB. In this we replace hectic lever arrangement for speed setting by giving input in the form of speed directly with the help of mobile phone, keypad or knob based on IOT and the energy will save up to 70%. A feedback device is used for monitoring whether the spindle rotate on given input value of speed or not. Lathe spindle rotate at the exact value, for this we used PID controller. In this research paper we basically discuss the software (made in SIMULINK) which is used in updating the conventional lathe machine.
Index Terms: IoT (internet of things), MATLAB, PID Controller, Three Phase Induction Motor and Variable Frequency Drive.

Scope of the Article: Machine Learning