Description
IC694BEM321 Horner Electric
высотой 3U, расположенный в раме управления под DSPX.
волоконно – оптический разъем на передней панели и передаются в модуль обнаружения заземления.
ABB: Запасные части для промышленных роботов серии DSQC, Bailey INFI 90, IGCT, например: 5SHY6545L0001 AC1027001R0101 5SXE10 – 0181, 5SHY3545 L0009, 5SHI3545L0010 3BHB013088 R0001 3BHE009681R0101 GVC750BE101, PM866, PM861K01, PM864, PM510V16, PPD512, PPPD113, PP836A, P865A, 877, PPP881, PPPP885, PPSL500000 4 3BHL00390P0104 5SGY35L4510 и т.д.
General Electric: запасные части, такие как модули, карты и приводы. Например: VMVME – 7807, VMVME – 7750, WES532 – 111, UR6UH, SR469 – P5 – HI – A20, IS230SRTDH2A, IS220PPDAH1B, IS215UCVEH2A, IC698CPE010, IS200SRTDH2ACB и т.д.
Система Bently Nevada: 350 / 3300 / 1900, предохранительные зонды и т.д., например: 3500 / 22M, 3500 / 32, 3500 / 15, 3500 / 23500 / 42M, 1900 / 27 и т.д.
Системы Invis Foxboro: Серия I / A, управление последовательностью FBM, трапециевидное логическое управление, обработка отзыва событий, DAC,
обработка входных / выходных сигналов, передача и обработка данных, такие как FCP270 и FCP280, P0904HA, E69F – TI2 – S, FBM230 / P0926GU, FEM100 / P0973CA и т.д.
Invis Triconex: Модуль питания, модуль CPU, модуль связи, модуль ввода – вывода, например 300830937214351B, 3805E, 831235114355X и т.д.
Вудворд: контроллер местоположения SPC, цифровой контроллер PEAK150, например 8521 – 0312 UG – 10D, 9907 – 149, 9907 – 162, 9907 – 164, 9907 – 167, TG – 13 (8516 – 038), 8440 – 1713 / D, 9907 – 018 2301A, 5466 – 258, 8200 – 226 и т.д.
Hima: модули безопасности, такие как F8650E, F8652X, F8627X, F8678X, F3236, F6217, F6214, Z7138, F8651X, F8650X и т.д.
Honeywell: Все платы DCS, модули, процессоры, такие как: CC – MCAR01, CC – PAIH01, CC – PAIH02, CC – PAIH51, CC – PAIX02, CC – PAON01, CC – PCF901, TC – CR014, TC – PD011, CC – PCNT02 и т.д.
Motorola: серии MVME162, MVME167, MVME172, MVME177, такие как MVME5100, MVME5500 – 0163, VME172PA – 652SE, VME162PA – 344SE – 2G и другие.
Xycom: I / O, платы VME и процессоры, такие как XVME – 530, XVME – 674, XVME – 957, XVME – 976 и т.д.
Коул Морган: Сервоприводы и двигатели, такие как S72402 – NANA, S6201 – 550, S20330 – SRS, CB06551 / PRD – B040SSIB – 63 и т. Д.
Bosch / Luxer / Indramat: модуль ввода / вывода, контроллер PLC, приводной модуль, MSK060C – 0600 – NN – S1 – UP1 – NNN, VT2000 – 52 / R900033828, MHD041B – 144 – PG1 – UN и т.д.
(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.
8307A Expansion / RXM Rack Power Supply, 230VACTRICONEX TRICON 8101 Expansion Rack
PR6423/00R-131+CON041 EPRO Vibration sensor
PFCL201C pillow block tension meter vertical load cell
PFEA111 conventional control unit
PFEL113: With DP port, can connect to 4 indenters
PFEL112: With DP port, it can connect two indenters
PFEL111: No DP port and can be connected to two indenters
PFCL301E mini paper tension vertical load cell
PFTL301E mini paper tension horizontal load cell
PFRL101D radial load cell
PR6423/10R-131+CON041 EPRO Pressure transducer
PFRL101C radial load cell
PFRL101A radial load cell
PR6423/10R-111+CON031 EPRO Robot control card
PR6423/008-110+CON021 EPRO sensor
PFTL201C 50KN 3BSE007913R50 Weight bearing sensor
DS200DCFBG1BLC GE Dc governor control board
CON011 9200-00001 EPRO cable
GPIB-140A 186135G-01 NI Memory storage module
SCYC51020 58052582G ABB Thermal resistance input module
PM865K01 3BSE031151R1 ABB Thermal resistance input module
FBM230 P0926GU FOXBORO Communication module
TRICONEX 8111N rack
TRICONEX 3501TN2 Servo control system
TRICONEX 3008N Digital signal output module
TRICONEX 8310N2 Converter main control board
TRICONEX 4352AN Rectifier module
DSDP140A Robot drive power supply
UFC721BE101 3BHE021889R0101 Technical parameters
PPC380AE01 HIEE300885R0001 PLC controller
UFC718AE01 HIEE300936R0001 ABB Safety control unit
UFC719AE01 3BHB003041R0001 ABB Control system
KUC720AE01 3BHB003431R0001 Controller master unit
07KT97 GJR5253000R4270 ABB System board card
07KT98C GJR5253100R028 ABB Control module card key
KUC711AE01 3BHB004661R0001Input control panel
07 KT 98 GJR5253100R0278 ABB controller
PFTL101B 5.0KN 3BSE004191R1 sensor
PFTL101B 5.0KN Cross sectional measurement Pressure magnetic indenter
PFTL101A 1.0KN ABB controller
PFTL101A 1.0KN 3BSE004166R1 ABB Tension control unit
3HNM07485-1/07 ABB Multi-function controller
3HNM07686-1 3HNM07485-1/07 ABB Robot axis calculation board
SYN 5201 A-Z ABB devices and systems
MVME172-263/260 SCSI & Ethernet Interface
MVME172-263/260 DCS system module
D674A906U01 ABB Electromagnetic Flowmeter
MSK050C-0300-NN-M1-UG1-NNNN motor
USIO21 TOSHIBA DC Signal Converter
USIO21 TOSHIBA industry switch
PM3326B-6-1-2-E Medium voltage circuit board
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