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Purchasing a new production machine: Have you explored all the alternatives?

Is it Really Necessary to Acquire a New Production Machine?

As the market accelerates, orders flood in, and demand increases, all manufacturers face this situation. Overtime becomes the norm and the question arises of how to meet demand without compromising quality or increasing lead times. In such a scenario, what can be done to adapt?

 

A common industrial issue

Monitoring machine usage and OEE (Overall Equipment Effectiveness) is a crucial starting point to uncover this "hidden factory" and identify opportunities for improvement. Unfortunately, many manufacturers find themselves with an OEE of less than 50%, which poses a major obstacle to their productivity.

To overcome this challenge, optimizing the use of your machines is crucial. Achieving this requires the missing link of real-time data recording. By capturing and analyzing the data generated by your machines, you can gain valuable insights into their actual usage, identify bottlenecks and inefficiencies, and thus improve their productivity.

Through data collection, you can optimize your processes, reduce downtime, improve your operators' skills, and enhance the maintenance of your equipment.

Rather than rushing to acquire new machines, it is therefore necessary to fully exploit your actual production data to maximize the use of your existing equipment. By identifying the hidden capabilities of your machine park, you can avoid unnecessary expenditures and improve the overall productivity of your plant.


 

A simple and cost-effective alternative

Monitoring machine usage and OEE (Overall Equipment Effectiveness) is a crucial starting point to uncover this "hidden factory" and identify opportunities for improvement. Unfortunately, many manufacturers find themselves with an OEE of less than 50%, which poses a major obstacle to their productivity.

 

To overcome this challenge, optimizing the use of your machines is crucial. Achieving this requires the missing link of real-time data recording. By capturing and analyzing the data generated by your machines, you can gain valuable insights into their actual usage, identify bottlenecks and inefficiencies, and thus improve their productivity.

 

Through data collection, you can optimize your processes, reduce downtime, improve your operators' skills, and enhance the maintenance of your equipment.

Rather than rushing to acquire new machines, it is therefore necessary to fully exploit your actual production data to maximize the use of your existing equipment. By identifying the hidden capabilities of your machine park, you can avoid unnecessary expenditures and improve the overall productivity of your plant.

 

Fully leverage your existing resources

Real-time machine data offers you the opportunity to detect problems impacting your activity, well beyond those you manually track today. Ultimately, purchasing a new machine may not be necessary as you already have capabilities in your workshop that you had not yet identified.

 

The more your machines remain underutilized, the less efficient your operators are and your production optimized. Instead of embarking on a massive investment project, leverage your data to improve the utilization of your existing equipment, allowing your machines to double or even triple their output.

 

With KEYPROD, you can get an instant view of the state of your machines, including a precise measure of their utilization, downtime, and cycle times. Integrating our IoT solutions into your machine park means gaining 10 to 15% in OEE from the first use.

 

In conclusion, optimizing the use of your existing machines is essential to meet growing demand without compromising quality or increasing lead times. Monitoring machine usage and analyzing real-time data are powerful tools for discovering the hidden capabilities of your machine park and significantly improving your productivity. Do not underestimate the potential of real-time data and explore solutions like KEYPROD to fully leverage your existing resources.

 

 

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