Maintenance people must be committed not only to keep the equipment operating by restoring it again after a failure but also to attain maximum uptime, performance and quality results and consequently, reducing costs. These key factors depends also on how the maintenance is performed.
Predictive maintenance plays a key role in production lines because sudden changes in performance can cause unplanned and costly downtimes as well as quality issues.
In recent years, the glass containers industry has made significant steps forward towards production quality improvement. But still, the challenge is to anticipate dimensional control at an earlier stage of the glassmaking process, with the purpose to immediately take the necessary actions and reduce scrap parts.
The automotive glass industry is currently experiencing a period of growth thanks to the evolution of the car design that are constantly including glass to realize more complex and fashion shapes. Electro-mobility and the autonomous driving advent push to increase the visual surface paying particular attention to its safety and weight to reduce the consumption.
Over the years, manufacturing industries have implemented several process improvements in order to guarantee high quality products and reduce costs, but there is still room for improvement. A huge potential is represented by data collection. Industries, such as aerospace or automotive, are realising the importance of data collection to improve operational efficiency. The process data, in fact, provides customers with highly effective tools in evaluation options and traceability, especially when it comes to forming and stamping technology of high-quality parts.
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