• 

  It is essential to check real-time data to detect abnormalities in automated machines.

  
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  Even mass production equipment under the same process can result in different process quality and product characteristics.

  
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  The (big) data generated by machines require intelligent analytics automation.

  

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  Collecting and preprocessing
  standardized online/offline data

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  Utilizing (Big) data processing techniques
  and applying data compression
  to improve DB performance

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  Aiming for a “0” process defect rate
  by realizing machine intelligence
  through real-time analysis/diagnosis

EES Module Composition

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  Feature 1.

  Self-diagnosis of machines and real-time management of data anomalies

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  Feature 2.

  Big data analytics using various open-source AI algorithms

• 

  Feature 3.

  Provides industry-specific functions for semiconductors, displays, secondary batteries, solar modules and more

• Semiconductor packaging firm achieves manufacturing intelligence

  A semiconductor packaging firm needed to build an efficient standard system for their aging MES solution and multi-factory production hierarchy. They classified production and defect track records as per work orders in the process and improved process response capabilities by informatizing worker experience and knowledge. With the QMS, yield reports and real-time monitoring of production equipment were established, and wafer map management functions were applied. Through Miracom's QMS, the customer gained the upper hand by responding to changes in manufacturing trends in the 4th Industrial Revolution through production, data automation, and manufacturing intelligence.

  • #MES
  • #EES
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