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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MTL838C MTL instrument analog transmitter
810-099175-011 LAM Interface board module
DSQC346G 3HAB8101-706B drive unit
5PC810. SX05-00 APC810 system unit
XV 430-12TSB-1-10 EATON 12.1″, TFT color
XV440-10TVB-X-13-1 EATON 10.4 “, TFT color
XV 430-10TVB-1-10 EATON 10.4 inches
XV442-57CQB-X-13-1 ESTON 5.7 inches
XV 432-57CQB-1-10 ESTON 5.7-inch touch screen
XV-440-12TVB-1-50 EATON
XV 440-12TSB-1-10 ESTON Touch panel
XV-440-12TVB-1-50 EATON Man-machine interface
XV 440-12TSB-X-13-1 ESTON 12.1″, TFT Color, i/r, Ethernet, USB, RS232, CANopen
XV442-57CQB-1-10 EATON 5.7 inch, Color, i/r, Ethernet, USB, RS232, CANopen
VE3008 CE3008 KJ2005X1-MQ1 12P6381X042 MQ Controller
05074-A-0122 05704-A-0121 05704-A-0131 honeywell Quad Relay Interface Card
136294-01 BENTLY 3500/62 I/O Module
P0926PA FOXBORO FBM224, FBM230, and FBM231 terminals
VBX01TA ABB Bus Extender
F3430 HIMA Input/output module
P0916FK FOXBORO cable
140471-01 3500/42M I/O Module
F3430 HIMA Relay module F 3430
3500/91-01-01(161204-01+161216-01)bently Communication Gateway Module
LENZE EPL10200-W includes EPZ-10203 CANPT010W3E
UNS0119A-Z,V1 3BHE030579R0001 Automatic voltage regulator
UNITROL 1020 3BHE030579R0003 Indirect Excitation System
UNS0119A-Z,V1 3BHE030579R0001 Automatic voltage regulator
LAIB V3.0_A00 034STN1-01-300-RS
LAIB V3.0_A00 034STN1-00-300-RS
ATKB_V5.0_A01 03ZSTI4-01-501
ATKB_V5.0_A01 03ZSTI4-00-501
FPB_V3.0_A01 03ZSTJ1-00-301-RS
DSPB_V4.0_A02 03ZSTI7-00-402-RS
PUIM V2.0 034STM4-00-200-RS
DUDT_DETECTION_V2.0_A01 03ZSTJ0-00-201-RS
IPB PCB V2.0_A01 03ZSTL6-00-201-RS printed circuit board
IPB PCB V2.0_A01 03ZSTL6-00-201-RS printed circuit board
149992-01 BENTLY 3500/33 calories Relay Output Module
IS220PVIBH1A 336A4940CSP16 GE Vibration Monitor Pack
RH916XZ foxboro FBM247 Fieldbus module
IS420UCSCH2A-C-V0.1-A Four core controller GE
5SHY3545L0010 3BHB013088R0001 3BHE009681R0101 GVC750BE101
FROSOFT MVI56E-MNETXT Enhanced communication module
REXROTH HDS02.2-W040N-HS12-01-FW Servo controller
DEUBLIN 904-120-188
810-234640-312 LAM Printed circuit board
SAIA 52030C10 PCD2.W200 Analog input module
VM600 XIO16T 620-002-000-113 620-003-111-112 VM600 XIO16T
200-595-031-111 VM600 CPUM modular CPU card
VM600 MPC4 200-510-071-113 200-510-111-034 machinery protection module
VM600 XMV16 600-003 620-001-001-116 condition monitoring module for vibration
VM600 IOC4T 200-560-000-018 200-560-101-015 voltage-drop adaptor
VM600 XIO16T 620-002-000-113 620-003-111-112 extended condition monitoring modules
NI-9853 C series CAN interface module
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