The client faced high and unpredictable costs because tools in production were being replaced either too late or too early. This led to unnecessary downtime and increased investment costs.
The goal was to make maintenance decisions based on facts rather than assumptions — and to create a more data-driven maintenance workflow.

We started the project by mapping all tools and their usage patterns. By collecting and analyzing production data, we calculated the actual utilization rate of each tool.
In collaboration with the production team, we identified optimized machine parameters and developed an application that automated data input through an RFID reader.
The application was integrated with the client’s existing systems using PowerFX, Power BI, SharePoint, and WPF, resulting in a solution that provides real-time insight into each tool’s lifecycle and condition.

Reduced tool investment costs and improved maintenance planning

Less operator time spent on manual data entry

Increased trust in production data and decision-making

Optimized machine performance through adjusted parameters