LINE QC SPECIALIST

Newly developed system to prevent NG (No good) products from being produced during the manufacturing process! Eliminate in-process defects

Thorough in-process inspections and automatic pre-shipment sorting which is Nano Seimitsu's specialty, will improve the accuracy of defective product detection, but will not reduce the number of defective products themselves. In order to fundamentally reduce defective products, it is necessary to take measures against the source of defective products in the process.

To stop the outflow of defective products of even one-in-a-million (zero PPM) without automatic sorting of all products, we can do "eliminate in-process defects.”

LQS is a system in which software monitors and controls employee work procedures, equipment (machines), and measuring instruments to ensure that products are always manufactured within specifications (within mass production standards) and safely, in accordance with internal manufacturing rules.


Three features of LINE QC SPECIALIST
(1) Automate monitoring operation of manufacturing site
(2) Automatic input of with digital measuring instruments and quality data judgment in real-time
(3) Big data analysis of measurement data

■ System details
・ Measurement instrument calibration management (calibration content, time)
= Software intervention in measuring instrument reliability
・ Divide between adjustment and start of mass production
= Systemize mass production approval
・ Divide between central control value setting during adjustment and control value setting during mass production = Focus on central control during adjustment
・ Convey the measurement location and measurement frequency to the operators and encourage them to measure the correct location with the correct control value.
・ If "measurement frequency cannot be observed", "measurement value has reached the control value", or "instrument calibration time has been exceeded", the software issues a warning
・The LINEQC system records all data during sampling-based mass production.
This big data can be analyzed and utilized to make more essential quality improvements.



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