About Bull Machines Pvt. Ltd.
Bull Machines Pvt. Ltd., a construction and agricultural equipment manufacturer on Trichy Road, Coimbatore, could not measure how much of a shift its welding machines spent actually welding. Utilisation was estimated from observation and manual logs, which meant supervisors were walking the floor to find out what a dashboard should have told them.
M-Connect gateways were fitted to the welding machines to capture arc-on and arc-off signals directly. The shop now sees live arc-running and idle state per machine, and shift-wise utilisation reports are generated automatically instead of estimated.
Our client is a globally recognized manufacturer specializing in construction and agricultural equipment. The organization operates advanced manufacturing facilities and maintains stringent production quality standards to support both domestic and international markets.
As part of the AV Group, which has more than six decades of industrial legacy, they focus on precision manufacturing, operational excellence, and continuous digital transformation. Within the fabrication shop floor, manual and robotic welding processes play a critical role in ensuring structural strength, dimensional accuracy, and production throughput. However, welding operations faced several operational challenges due to the absence of structured digital monitoring.
The problem: nobody knew the real arc-on time
Real-time monitoring of welding machine operational status — specifically arc running and idle conditions
Industrial IoT gateways connected to welding machines for automatic arc-state detection
Centralized dashboards enabling supervisors to monitor machine states across the shop floor
BEFORE M-CONNECT: WELDING MACHINE ARC-TIME AND UTILIZATION WERE ESTIMATED MANUALLY, NOT MEASURED
What the fabrication shop looked like before
Welding operations faced several operational challenges due to the absence of structured digital monitoring.
Limited Real-Time Machine Visibility
Welding machine operations were largely tracked through manual logs and operator inputs, resulting in limited real-time visibility into machine operating conditions.
Inaccurate Machine Utilization Tracking
The absence of automated monitoring made it difficult to accurately measure actual arc running time and idle time across shifts.
Delayed Operational Insights
Production data collected through manual records often resulted in delayed and inconsistent information, making operational analysis and decision-making difficult.
What was installed, and how
To address these challenges, Maestro Technology Services Pvt. Ltd. deployed the M-Connect Industrial IoT platform across the welding shop-floor environment. The solution was designed to enable real-time monitoring of welding machine operational status, specifically focusing on arc running and idle conditions. The solution was implemented with minimal disruption to production and integrated seamlessly into the existing shop-floor infrastructure.
Industrial IoT Gateways
Welding machines connected via industrial-grade IoT gateways — no machine modification required.
Arc-State Detection
Automatic detection of arc-on and arc-off events, providing accurate machine activity data.
Centralized Dashboard
Live operational status visible to supervisors and production teams across the facility.
M-CONNECT AUTOMATICALLY DETECTS ARC-ON AND ARC-OFF EVENTS — SHIFT BY SHIFT, MACHINE BY MACHINE
The M-Connect Technology Stack
Machine signals captured, processed, and presented as actionable shop-floor intelligence.
Industrial IoT Gateway Integration
M-Connect industrial IoT gateways were installed at each welding machine to capture electrical signals corresponding to machine operating states. This enabled automatic, continuous detection of arc-on and arc-off events without requiring manual operator input or machine modification.
Live Machine Activity Capture
Machine activity was monitored in real time, distinguishing between arc-running (productive) and idle states for each welding machine across every shift. This provided operational teams with an accurate picture of actual machine utilization vs. available production time — shift by shift, machine by machine.
Centralized Operational Dashboard
All machine-level data was aggregated into a centralized M-Connect dashboard accessible to supervisors and operational teams. The dashboard provided visibility into machine states across the welding shop floor, enabling supervisors to identify underperforming machines, excessive idle periods, and operational irregularities without physically walking the floor. Reports were available in shift-wise and daily formats, supporting structured operational review and continuous improvement.
M-Connect dashboard — real-time welding machine state monitoring across shifts
What the Deployment Delivered
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Real-time visibility into welding machine arc-on and idle states
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Automated utilization tracking — eliminating manual estimation
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Shift-wise and daily reporting for operational review
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Centralized dashboards accessible to supervisors without floor walks
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A structured foundation for continuous welding productivity improvement
What changed for the supervisors
The deployment of M-Connect across the welding shop floor replaced manual, inconsistent tracking with structured, automated machine monitoring — providing operational teams with the data needed to drive measurable improvements in welding machine utilization and shop-floor productivity.
The honest version of this result is not a percentage. It is that a supervisor who previously walked the shop to see which welding stations were live now opens one screen, and the daily utilisation report is produced without anyone compiling it. What the plant does with that number is a separate decision — but they now have one. The same signals feed our machine monitoring software and production monitoring software, and the background is in tracking welding machine utilisation with Industrial IoT.
"From manual observation to digital shop-floor intelligence — welding machine operations are now monitored in real time, shift by shift, machine by machine."