Figure 5: Software can recognize defects
Figure 6: Nominal Actual Correction Continued from pg 23
companies increase their value is by providing various metrologies such as Porosity Analysis, Nominal-Actual Comparison, Wall thickness and even oxide detection. Currently, these kinds of metrology require an operator to input certain criteria and values to enable the software to output the analysis. In the future, AI will be able to detect and learn what criteria and values to input and the operator only needs to push a button that will do the desired metrology.
24 ❘ July 2020 ®
Future of Quality Control Now, what does the future of Quality Control look like if it’s already good? Currently humans are still driving the “ship” with the help of these advanced technologies. However, AI will soon take the driver’s seat and humans will be the passenger. AI will eventually be able to learn how to use six sigma and lean manufacturing overtime when given enough data and has run enough processes. It can point to certain robotic movements and limit movement inefficiencies that it may notice to reduce the time it takes the robot to move a part. It can suggest factory set
up improvements overtime to maximize production rates even. Soon enough, companies will be able to share their data on the Cloud and with the emergence of blockchain and be able to track certain information companies need. Perhaps all the data around the world will eventually be shared in a unified data repository and companies can leverage that data in their own companies. These are the kinds of Quality Control methods that can be made possible and eventually this process itself will be completely intelligent and autonomous.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32