Description
hardware flow control. It is an ideal choice in the field of industrial automation.
(2) Data collection and traceability issues. Data collection issues often occur, and many assembly lines lack “end-to-end traceability.”
In other words, there are often no unique identifiers associated with the parts and processing steps being produced.
One workaround is to use a timestamp instead of an identifier. Another situation involves an incomplete data set. In this case, omit
incomplete information parts or instances from the forecast and analysis, or use some estimation method (after consulting with manufacturing experts).
(3) A large number of features. Different from the data sets in traditional data mining, the features observed in manufacturing analysis
may be thousands. Care must therefore be taken to avoid that machine learning algorithms can only work with reduced datasets (i.e.
datasets with a small number of features).
(4) Multicollinearity, when products pass through the assembly line, different measurement methods are taken at different stations
in the production process. Some of these measurements can be highly correlated, however many machine learning and data mining
algorithm properties are independent of each other, and multicollinearity issues should be carefully studied for the proposed analysis method.
(5) Classification imbalance problem, where there is a huge imbalance between good and bad parts (or scrap, that is, parts that do not
pass quality control testing). Ratios may range from 9:1 to even lower than 99,000,000:1. It is difficult to distinguish good parts from scrap
using standard classification techniques, so several methods for handling class imbalance have been proposed and applied to manufacturing analysis [8].
(6) Non-stationary data, the underlying manufacturing process may change due to various factors such as changes in suppliers
or operators and calibration deviations in machines. There is therefore a need to apply more robust methods to the non-stationary
nature of the data. (7) Models can be difficult to interpret, and production and quality control engineers need to understand the analytical
solutions that inform process or design changes. Otherwise the generated recommendations and decisions may be ignored.
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3BHB030310R0001 IGCT module ABB
5SHY4045L0006 IGCT module ABB
5SXE08-0167 IGCT module ABB
AC10272001R0101 IGCT module ABB
5SHY5045L0020 IGCT module ABB
5SHY5045L0020 AC10272001R0101 ABB
5SHY5045L0020 5SXE08-0167 ABB
5SHY5045L0020 5SXE08-0167 AC10272001R0101
5SHY5055L0002 3BHE019719R0101 GVC736BE101
5SHY5055L0002 GVC736BE101 ABB
5SHY5055L0002 3BHE019719R0101
GVC736BE101 IGCT module ABB
3BHE019719R0101 IGCT module ABB
5SHY5055L0002 IGCT module ABB
5SXE10-0181 IGCT module ABB
AC10272001R0101 IGCT module ABB
5SHY6545L0001 IGCT module ABB
5SHY6545L0001 5SXE10-0181 ABB
5SHY6545L0001 AC10272001R0101
5SHY6545L0001 AC10272001R0101 5SXE10-0181
3BHE024855R0101 UFC921A101 ABB
3BHE024855R0101 Industrial module ABB
UFC921A101 Industrial module ABB
HIEE300910R1 Industrial module ABB
UFC092BE01 Industrial module ABB
UFC092BE01 HIEE300910R1 ABB
UFC718AE101 HIEE300936R0101 HIEE410516P201AENDE
UFC718AE101 HIEE410516P201AENDE
UFC718AE101 HIEE300936R0101 ABB
HIEE410516P201AENDE Main control board
HIEE300936R0101 Main control board ABB
UFC718AE101 Main control board ABB
3BHB000272R0001 Main control board ABB
3BHB003041R0001 Main control board ABB
UFC719AE01 Main control board ABB
UFC719AE01 3BHB000272R0001 ABB
UFC719AE01 3BHB003041R0001 ABB
UFC719AE01 3BHB003041R0001 3BHB000272R0001
UFC721AE 3BHB002916R0001 ABB
3BHB002916R0001 Main control board ABB
UFC721AE Main control board ABB
3BHE021889R0101 Main control board ABB
UFC721BE101 Main control board ABB
UFC721BE101 3BHE021889R0101 ABB
3BHE004573R1142 Main control board ABB
UFC760BE1142 Main control board ABB
UFC760BE1142 3BHE004573R1142 ABB
UFC760BE141 3BHE004573R0141 ABB
3BHE004573R0141 Main control board ABB
UFC760BE141 Main control board ABB
3BHE004573R0142 Main control board ABB
UFC760BE142 Main control board ABB
UFC760BE142 3BHE004573R0142 ABB
UFC760BE41 3BHE004573R0041 ABB
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