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QUALITY DATA | INTERNET OF THINGS

To be able to create reports about the produced quality additional data from the shop floor was needed. Although it would have been perfect to get this data directly from the machines it has to be noted that the vast majority of machines used by discrete manufacturers is not able to distinguish between parts of good quality and scrap.

Goal:

  • Contextualize results of quality assurance operations with work order and machine data

This information usually is gathered in an own subsequent Quality Assurance (QA) operation that includes tasks like visual inspection and measurements with special equipment. To be able to contextualize the result of the QA operation with the data acquired from the machines an extension to the customer’s program for Operational Data Acquisition (ODA) was created. Similar to the dialog to start and stop work orders the operator scans the work order traveler to identify the correct operation. Instead of a dialog for changing the work order or its state the program shows the machine’s output quantity for the operation and enables the user to assign a subset as rework or scrap if necessary. In addition a reason for the assignment can be selected.

Contextualization of the result of the QA operation with machine data has a huge benefit. Both data acquisition techniques, CNCnetPDM and OPC have the ability to collect several process parameters such as feed rate, spindle speed, temperatures or pressure when reading machine data. Combined with the result of the QA operation this enables to detect possible reasons for bad quality at the machine side. On the other hand the collected process parameters can be used to fulfil documentation obligations.

Functions:

  • Contextualization of results of subsequent quality assurance operation with work order and machine related data

Benefits:

  • Created relationship between quality- machine- and work order data
  • Enabled collection of process data for documentation obligations
  • Reduced costs for implementation by using the customers solution for acquisition of quality assurance data

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https://www.inventcom.net/success-stories/internet-of-things/quality-data

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Modified: 2015-11-22