Advancing Smart Manufacturing through Industrial IoT: Enhancing Operational Efficiency and Predictive Maintenance

Abstract

The Internet of Things has become influential force in Smart Manufacturing. Our study focusses on advanced data analytics making it possible by data collection at real time from sensors linked with each other and various equipment, which helps manufacturers optimise resource allocation and expedite workflows. Through case study we have created IIOT-based system at a medium sized manufacturing facility. Utilising cloud-based analytics and machine-to-machine(M2M) communication, this system optimises energy use, forecasts component failures, and keeps an eye on machine-health. As a part of our process, wireless sensor networks (WSNs) are deployed to collect critical data points including pressure, temperature, and vibration. To prevent possible machine breakdowns, these data are processed using algorithms. The findings show significant cost savings, operational efficiency gains and the predictive maintenance with high accuracy rate. Initiatives to optimise resources also resulted in decrease in energy use. The study concludes by highlighting the potential of IIOT in improving operational effectiveness and prolonging equipment lifespan in Smart Manufacturing. IIOT is a key technology for the future of industrial operations by enabling manufacturers to attain previously unheard levels of efficiency, sustainability and cost effectiveness through the use of real time data and predictive analytics. The effective deployment of IIOT has opened door for additional study into its uses in different industries, which helps create creative solutions that can boost competitiveness and growth in the global economy.