The commercial foundry in Turnov, which successfully implemented basic modules of the manufacturing execution system (MES) using EDIH NEB in 2024, reports its first tangible results. The installation of measuring devices and their connection to the planning system has improved efficiency and enabled better management of production and shift operations.
“The efficiency was evident immediately after the installation of the technology. We have data at our disposal that helps us identify weaknesses in production and take specific measures to improve them,” said Pavel Světlík, the company’s director. The system generates regular reports, which are a valuable tool, especially for new employees, who learn to analyse operations and propose improvements based on them.
Working with data as a new challenge
Although the technologies are functional and have met expectations, the company is now emphasising more systematic use of the available data. “It’s up to us now – we have to learn how to work with the data, evaluate it and make full use of it for further development,” adds the foundry director. To ensure the effective use of data, the company plans to expand its team with an employee who will be responsible for analysis and proposing specific measures. There is also a need for consultation or methodological support in implementing analytical tools.
The way forward: stabilisation and further development
At this stage, the foundry is focusing on stabilising processes and maximising the use of modules that have already been implemented. “The benefits are evident both in production data and in the attitude of employees, who have embraced the technology and are actively working with it, which is very important. The foundry does not currently plan to further expand its digitalisation efforts – the priority is to make full use of what has already been implemented. However, the company’s management is considering the possibility of expanding its cooperation with EDIH NEB and Softli, particularly in the area of monitoring tools and predictive analytics,” summarises Pavel Světlík.
