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.
HD-522 SHINBORY DENSHI Heater Control Switch Panel
321131-A01 337672-A01 Allen-Bradley Interface Board
394877-A02 4002604070 Allen-Bradley PC board
314066-A02 Allen-Bradley PC POWER SUPPLY BOARD
2711-K10C1 Allen-Bradley PanelView 1000 Standard Operator Terminal
1336-SN-SP10A 74101-363-51 Allen-Bradley component of the Bulletin 1336 drives
GPD506V-B004 MAGNETEK AC DRIVE
1771-OJ/A Allen-Bradley pulse output expander module
GVC704AE01 5SXE05-0152 3BHB003230R0101 3BHB003023P201 ABB
GDC801B101 3BHE051592R0101 ABB
1794-IB16 Allen-Bradley Flex IO DC Input Module
2711-K5A8 Allen-Bradley Panelview 550 Standard Operator Terminal
IC660BBA100 GE analog I/O Block
DSDX453 5716075-AN ABB Remote In / Out Expansion Unit
135462-01 Bently Nevada PLC module
132419-01 Bently Nevada PLC module
132417-01 Bently Nevada PLC module
2711P-T6C5A Allen-Bradley Panelview Plus 600 series operator interface terminal
1771-OFE2 Allen-Bradley analog output module
1771-IR Allen-Bradley PLC5 Resistance Temperature Detector (RTD) input module
330100-90-00 Bently Nevada Proximitor Sensor
1771-IFMS Allen-Bradley intrinsically safe fast millivolt input module
1771-OBDS Allen-Bradley digital output module
1771-IBN Allen-Bradley PLC5 Discrete Input module
1771-CFM Allen-Bradley configurable type of flow meter module
1771-ACN Allen-Bradley ControlNet adapter module
1402-LS51 Allen-Bradley Line Synchronization Module
WR-D4004 MD-D4014B RELIANCE
A2H254-16-RH A2H254-16 Enterasys Networks Network Switch
TK457V050 3BSE004394R1 ABB Cable assembly
SCXI-1000 NI Low-Noise, 4-Slot, AC Chassis
SCXI-1304 NI –3 dB Cutoff Frequency, 60 V, AC/DC Coupling Terminal Block
PCIH38F300A1 UPWRA-KW3M2UPWR Positronic Rectangular power connector
DSCS150 57520001-FY ABB GCOM Communication Unit
TC-CCR014 97321174-A01 HONEYWELL Redundant Net Interface
SCXI-1600 NI 16-Bit, 200 kS/s Sampling Rate, Data Acquisition Module
P0926AH-B FOXBORO Power Supply
SCXI-1162HV NI 32-Channel, Isolated AC/DC, Digital Input Module
P0973CN FOXBORO FIELDBUS COMMS BASE MODULE
IC697BEM731Z GE Bus Controller Module
ESA-700 EPSD-0375-1108 ALSTOM Limelight Flame Signal Analyzer
9200-06-01-10-00 Bently Nevada 9200 watt vibration probe
MVI56-MDA4 PROSOFT MDA Scientific CM4 Platform Master Module
MVI56-LTQ PROSOFT Limitorque Valve Network Interface Module
PQV80020041 VALMET
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