Abhinand Maurya
"IoT Engineer
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About
Developing IoT-ready automation solutions for injection molding.Integration of MQTT and cloud connectivity for real-time monitoring.VFD system configuration and optimizing motor control.Leading multiple IoT-enabled automation projects.Mention technologies and tools you used (Node-RED, Siemens S7-1200, AWS IoT, Modbus TCP/IP).
Experience
You are an IoT Engineer and Industrial IoT Automation Specialist with 4 years of experience bridging industrial automation and modern IoT technologies. Key professional roles include:Developing IoT-ready automation solutions for injection molding using INVT controllers and Innovance drives.Designing HMI dashboards with predictive maintenance alerts achieving 95% uptime.Integrating MQTT and Modbus TCP/IP protocols for data collection and cloud connectivity.Reducing cycle time by 15% and improving energy efficiency by 20% through optimized automation.Programming Siemens S7-1200 PLCs and INVT controllers to increase system efficiency by 20%.Leading 50 automation projects with IoT-readiness enabling remote monitoring.Configuring VFD systems for precision motor control.Implementing predictive maintenance systems and standardizing automation to reduce project delivery time by 30%.
Education
You are an IoT Engineer and Industrial IoT Automation Specialist with 4 years of experience bridging industrial automation and modern IoT technologies. Key professional roles include:Developing IoT-ready automation solutions for injection molding using INVT controllers and Innovance drives.Designing HMI dashboards with predictive maintenance alerts achieving 95% uptime.Integrating MQTT and Modbus TCP/IP protocols for data collection and cloud connectivity.Reducing cycle time by 15% and improving energy efficiency by 20% through optimized automation.Programming Siemens S7-1200 PLCs and INVT controllers to increase system efficiency by 20%.Leading 50 automation projects with IoT-readiness enabling remote monitoring.Configuring VFD systems for precision motor control.Implementing predictive maintenance systems and standardizing automation to reduce project delivery time by 30%.
