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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MRU-M-MB3 KONGSBERG motion reference unit
140XTS00200 Controller Spiral Terminal Block
RMP201-8 Kongsberg Remote Multipurpose I/O
3500/22M 138607-01 Transient Data interface module
216NG61A HESG441633R1 HESG216875/K Input/Output module
A4H254-8F8T P0973JP Enterasys A4 fast Ethernet switch
CI860K01 3BSE032444R1 Field bus HSE interface
0-57210-31 115/230 VAC phase 1 main circuit board
The 1336S-MCB-SP1B is used for the 1336 PLUS driver PC main control board
0-52712-7 PC output frequency module card
05701-A-0512 Rack components in the 8-channel rear aisle
T8850 ICS Trusted 40-channel analog or digital output FTA
TRICON 3481 TMR analog output module
T8830 ICS Trusted 40-channel analog input FTA
60M100-00 Bently Nevada Monitor Controller
VT-VPCD-1-15/V0/1-P-1 Rexroth Digital control amplifier
SCYC51020 58052582/G Data acquisition module
KJ2003X1-BB1 m series MD Plus controller
RELIANCE 0-57100 Control logic module
0-57170 RELIANCE regulator module
S20660-SRS S200 servo drive
CI854K01 3BSE025961R1 Communication interface module
IC695CPU320-HS Controller module
PFTL201C 50KN 3BSE007913R50 Pressure sensor Pillow weight sensor
146031-01 Transient Data Interface I/O Module 3500/22M
G123-825-001 buffer amplifier MOOG
Allen-Bradley MSR241P Modular Safety Relays
SCYC51020 58052582G trigger pulse board
PM865K01 3BSE031151R1 PM867 Processor Unit HI
PCD232A101 3BHE022293R0101 AC800 PEC Excitation module
GPIB-140A 186135G-01 fiber GPIB expander
DS200DCFBG1BLC Power supply board Mark V series
TRICON 8310N2 Power Supply Modules
TRICON 3501TN2 Digital output module
TRICON 4352AN Process Safety System communication module
PR6423/008-110+CON041 electric sensor
TRICON 3008N Central processing unit 3008
5X00500G01 Analog input module
PR6423/00R-010+CON031 Electric sensor
UR8LH GE Multilin UR Series CT/VT Module
UR6CH GE Multilin Digital Input Output I/O Module
UR9EH GE Control module
UR6UH GE CPU module
EGCP-3 8406-113 WOODWARD Digital Control Interface Panel
ABB PFCA401SF 3BSE024387R4 Control Unit, 4 ai , profibus
UNIOP ETOP306 300 HMI panels
MTL MTL4549Y Intelligent isolated driver
DELTATAU CLIPPERT3 driver
NSSM01 Bailey Net 90 Superloop serial module
IISAC01 analog control station
NIMP01 Multifunctional processor terminal module
NTR002-A Multifunctional processor terminal module
NTLS01 Multifunctional processor terminal module
saia-burgess PCD3.M5540 CPU basic module
INICT01 ABB via the I/O expander bus
125800-01 Keyphasor I/O module
133819-01 3500/60 Internal terminal of I/O module
3500/53 133388-01 Used as an overspeed protection system
PU512V2 3BUR001401R1 Real-Time accelerator board
216DB61 HESG324063R100 HESG216882/A Analog Output module
ABB REG216 microcomputer generator
216EA61b HESG324015R1 KHESG324258R3I Analog output module
TBF120/7R MTS for brushless speed control
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