Monitoring and Controlling of Loom Parameters Using Job Shop Scheduling Algorithm

Power loom plays a crucial role in the industrialization of weaving. Manual controlling of looms may cause human errors, consumes more time, labor-intensive, etc. This research work proposes a unit to monitor the parameters of a loom (current, voltage, ON/OFF status, etc.,) and updates it to the control unit using a mobile application and also by implementing efficient Job Shop Scheduling algorithm like Particle Swarm Optimization. This also works with the cotton dust level, which can be the greatest health hazard for the workers and also to ensure safety in terms of health aspects. Various sensors like voltage sensors, current sensors, temperature sensors, and IR sensors are used with Node MCU to monitor the parameters like current, voltage, power and temperature of looms, dust level, and detection of human interventions and notify in case of any error with both mobile application and alarm using a relay. Implementing this in the textile industry can improve production efficiency, quality check, predictive maintenance, and the safety of workers.