Use Case

Data-driven Maintenance

Transform machine maintenance with real-time and historical data.

Situation

A machine operator at a metal fabrication plant oversees a critical CNC machine. The CNC machine often experiences unexpected downtime.

This impacts production schedules and causes the operator stress. To address this, the operator now has access to the MIP dashboard. The dashboard provides real-time and historical machine data for the CNC.

Action

  • Immediate Downtime Diagnosis. During a routine operation, the CNC machine suddenly stops. Instead of waiting for a technician, the operator accesses the MIP dashboard to diagnose the issue. The dashboard displays a history of downtime incidents, highlighting common causes such as coolant temperature spikes, spindle overload, and tool misalignments. By comparing the current parameters with past incidents, the operator quickly identifies a pattern: the coolant temperature has exceeded its optimal range.
  • Real-Time Parameter Monitoring. The operator reviews the live data on the MIP dashboard. They notice that the coolant temperature has been gradually rising over the past hour. This correlates with the machine's previous shutdowns. The operator identifies that the machine's cooling system needs immediate attention to avoid a shutdown.
  • Proactive Maintenance Scheduling. The operator uses the historical data to determine that the coolant system requires more frequent maintenance. They log a maintenance request, detailing the issue and referencing the specific historical data that highlights the recurring problem. This proactive approach ensures the maintenance team addresses the root cause rather than just fixing the immediate symptom.

Result

  • Reduced Downtime. The operator reduces the machine's downtime by 50% through a quick and accurate diagnosis. The faster resolution prevents production delays and ensures the operator can meet their production targets.
  • Improved Machine Health. The CNC machine is kept in optimal condition by regular monitoring and early detection of rising coolant temperatures. The proactive maintenance reduces wear and tear. This extends the machine's lifespan and ensures more reliable operation.
  • Enhanced Operator Efficiency. With access to real-time and historical data, the operator becomes more self-reliant and efficient in handling machine issues. They are less dependent on the maintenance team for routine issues. As a result, they feel empowered and more satisfied with their job.
  • Data-driven Maintenance Implementation. A maintenance schedule is implemented using the data surfaced by the operator. The plant moves from reactive to proactive maintenance, further reducing unexpected downtimes and improving overall production efficiency.
  • Cost Savings. The reduced downtime, improved machine health, and proactive maintenance schedule result in significant cost savings for the plant. The investment in the MIP dashboard proves to be highly cost-effective, demonstrating a clear return on investment through enhanced operational efficiency.
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