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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SC510 3BSE003832R1 | ABB | communication module
PM511V08 3BSE011180R1 | ABB | processor module
PFSA140 3BSE006503R1 | ABB | Roll Supply
DSDX452L | ABB | S400 input/output
SD812F 3BDH000014R1 | ABB | power module
07DC92 GJR5252200R0101 | ABB | I/O module
DSPU131 3BSE000355R1 | ABB | MA200 interface board
ICSI16E1 FPR3316101R0034 | ABB | binary input unit
EHDB280 | ABB | power contactor
UDC920AE01 3BHE034863R0001 | ABB | power module
REX521GHHGSH51G | ABB | Feeder protection device
LDSTA-01 | ABB | motor driver
GFD563A101 3BHE046836R0101 | ABB | central processing unit
3HAC025338-006 | ABB | Main Servo Drive Unit
SD24D/492896201 | ABB | Expansion unit
5SGX1060H0003 | ABB | igct module
5SHY3545L0020 3BHE014105R0001 | ABB | Thyristor IGCT module
SDCS-FIS-3A DCF803-0035 | ABB | excitation plate
DCF803-0050 DCF503B0050 DCF503A0050 | ABB | Excitation module
DCF503B0035 DCF504B0050 | ABB | excitation plate
NPBA-82 AINT-14C AGBB-01C | ABB | adapter
81EU01H-E | ABB | safety controller
DAPC100 | ABB | DAPC 100 3ASC25H203 Printed circuit board
DAPU100 | ABB | DAPU 100 5FSE705320-2 Control Board Kit
DAPU100 | ABB | DAPU 100 3ASC25H204 I/O driver board
DATX110 | ABB | 3ASC25H208 Pulse Transformer Board
DATX111 | ABB | DATX 111 3ASC25H224 control board
DATX120 | ABB | 3ASC25H210 I/O board Remote
AI930B | ABB | 3KDE175512L9300 S900 Series Analog Input Module
AI931B | ABB | 3KDE175512L9310 S900 Series Analog Input Module
AI950B | ABB | 3KDE175522L9500 S900 Series Temperature Input Module
AO910B | ABB | 3KDE175532L9100 S900 series analog output module
AO920B | ABB | 3KDE175532L9200 S900 series analog output module
AO930B | ABB | 3KDE175532L9300 S900 series analog output module
CB220B | ABB | 3KDE175612L2210 power supply
SA911B | ABB | 3KDE175612L9110 controller module
CI920N | ABB | 3BDS014112 Communication module
TU921N | ABB | 3KDE175113L9210 Backplane supports 16I/O modules
DX910N | ABB | 3KDE175313L9100 Switch I/O Modules
SA920N | ABB | 3BDH000600R1 Analog input module
DO910N | ABB | 3KDE175323L9100 Switch output module
DO930N | ABB | 3BDS014114 Analog input module
DP910N | ABB |3KDE175363L9100 Frequency Input Module
AI910N | ABB | 3KDE175513L9100 Analog input module
AI930N | ABB | 3KDE175513L9300 Analog input module
AI931N | ABB | 3KDE175513L9310 Analog input module
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