Description
XVS-460-57MPI-1-10VAR14 Многоточечный сенсорный дисплей EATON
современными требованиями дизайна. Как и XV303, конденсаторный многоточечный сенсорный дисплей поддерживает реализацию
современного пользовательского интерфейса (управление жестами)
и предлагает 7 – и 10 – дюймовые дисплеи, в том числе версии с высоким соотношением сторон 16: 9.
просто и требует меньше компонентов и инженерных работ, чем традиционная проводка. SmartWire – DT интегрирует связь и ввод / вывода
непосредственно в устройства управления, отображения и переключения, открывая новые возможности для инновационных и экономичных решений.
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.
(5) Perform predictive maintenance, analyze machine operating conditions, determine the main
causes of failures, and predict component failures to avoid unplanned downtime.
Traditional quality improvement programs include Six Sigma, Deming Cycle, Total Quality Management (TQM), and Dorian Scheinin’s
Statistical Engineering (SE) [6]. Methods developed in the 1980s and 1990s are typically applied to small amounts
of data and find univariate relationships between participating factors. The use of the MapReduce paradigm to simplify data processing in
large data sets and its further development have led to the mainstream proliferation of big data analytics [7]. Along with the development of
machine learning technology, the development of big data analytics has provided a series of new tools that can be applied to manufacturing
analysis. These capabilities include the ability to analyze gigabytes of data in batch and streaming modes, the ability to find complex multivariate
nonlinear relationships among many variables, and machine learning algorithms that separate causation from correlation.
Millions of parts are produced on production lines, and data on thousands of process and quality measurements are collected for them, which is
important for improving quality and reducing costs. Design of experiments (DoE), which repeatedly explores thousands of causes through
controlled experiments, is often too time-consuming and costly. Manufacturing experts rely on their domain knowledge to detect key
factors that may affect quality and then run
DoEs based on these factors. Advances in big data analytics and machine learning enable the detection of critical factors that effectively
impact quality and yield. This, combined with domain knowledge, enables rapid detection of root causes of failures. However,
there are some unique data science challenges in manufacturing.
(1) Unequal costs of false alarms and false negatives. When calculating accuracy, it must be recognized that false alarms
and false negatives may have unequal costs. Suppose a false negative is a bad part/instance that was wrongly predicted to
be good. Additionally, assume that a false alarm is a good part that was incorrectly predicted as bad. Assuming further that
the parts produced are safety critical, incorrectly predicting that bad parts are good (false negatives) can put human lives
at risk. Therefore, false negatives can be much more costly than false alarms. This trade-off needs to be considered when
translating business goals into technical goals and candidate evaluation methods.
PR6424/003-030 EPRO DCS controller Brand new stock
PR9268/300-000 EPRO Current current probe Brand new original
PR9376/010-011 epro Current current probe Brand new with box
PR9376/20 EPRO ER bus cable
RSM020 EPRO External shaft main board
SDM010 EPRO Inventory module Brand new stock
MMS6823R EPRO DCS system module
MMS3120/022-000 EPRO Axial vibration displacement monitoring module
PR9268/300-000 EPRO Adapter terminal module
MMS3120/022-000 EPRO Backplane connector
MMS6312 EPRO TSI speed card
MVI56-MNET PROSOFT Programmable control system
MVI56-MNETC PROSOFT Servo control panel
MVI56-MNETR PROSOFT System module
MVI56E-MCM PROSOFT PLC control system
MVI69-PDPMV1 PROSOFT Digital input module
MVI69L-MBS PROSOFT I/O communication modules
PLX32-EIP-SIE PROSOFT DCS system
PTQ-PDPMV1 PROSOFT Analog output module
RLX2-IHNF-A PROSOFT Serial communication module
149986-01 Spare 16-Channel Relay Control Module
4118 TRICONEX 4118 Enhanced Intelligent Communication Module (EICM) Isolated
8311 TRICONEX 8311 control system power supply 24VDC
4108 TRICOENX 4108 Enhanced Intelligent Communication Module (EICM) Non-Isolated
8310 TRICONEX 8310 control system power supply 120VAC/VDC
7518-1 TRICOENX 7518-1 Communication Network Module / ISA Bus
4508 TRICOENX 4508 High Speed Channel Interface Module (HIM)
8301A TRICONEX 8301A main frame power supply, 24VDC
8300A TRICOENX 8300A main frame power supply, 115VAC/DC
3500/33 BENTLY Relay 16 channel module
4400 TRICONEX 4400 Safety Management Module (SMM)
8302A TRICOENX 8302A main frame power supply, 230VAC
8106 TRICONEX 8106 Empty Terminal Slot
3500/50 BENTLY Rotating speed module
8306A TRICOENX 8306A Expansion / RXM Rack Power Supply, 24VDC
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