SUCCESS STORY

THE TOOLING TRANSFORMATION JOURNEY OF SAMSUNG

Samsung has faced problems with its mold monitoring. Today, although they are still developing their technology, much has improved through the digitalization of mold counters. eMoldino solution likewise provides the necessary hardware and software to easily and conveniently digitalize the molds.

Learn why tooling monitoring is important.

  • Samsung Electronics chose eMoldino to replace their manual data-gathering and entry systems but later learned that the solution can also help maximize mold longevity, predictive maintenance, and cost optimization.

  • Samsung used the mold’s actual shot counts and designed shot count information to determine their molds’ utilization rates, thereby identifying the accurate lifespan of their molds.

  • Samsung created a rigorous method of scheduling predictive maintenance based on mold condition information. Predictive maintenance is more beneficial than corrective maintenance, as the downtime involved in the latter is too costly--costing an average of $22,000 per minute of downtime in the auto industry.

 

  • Through eMoldino, Samsung was able to save an estimated $0.4 billion over the years by approximately cutting 50% of their annual mold production. This was possible by enabling improved forward planning and efficiency of Samsung’s management of their molds and suppliers.

  • Before working with eMoldino, Samsung would often distribute their molds to suppliers, lose track of them, and discover them collecting dust in completely unexpected supplier facilities. After the implementation of eMoldino wireless IOT mold, they could then track down their mold’s locations and prevent them from getting lost.

  • Samsung did a full crossover from using preventive maintenance to predictive maintenance. The benefits acquired are many but most importantly risk migration and cost optimization.

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  • Today, Samsung is in working with eMoldino and still testing and developing the software and hardware to improve their predictive maintenance and quality management through the implementation of AI & machine learning to embrace tooling industry 4.0.

The impact of AI & Machine Learning on tooling.

 

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