Description
IS200TBAIH1CCC GE Steam Turbine System
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 Leveraging big data tool chains
After the data collected from the manufacturing product value chain is stored in the database, a data analysis system is required to analyze the data.
The manufacturing data analysis system framework is shown in Figure 1. Data is first extracted, transformed, and loaded (ETL) from different
databases into a distributed file system, such as Hadoop Distributed File System (HDFS) or a NoSQL database (such as MongoDB). Next,
machine learning and analytics tools perform predictive modeling or descriptive analytics. To deploy predictive models, the previously mentioned tools
are used to convert models trained on historical data into open, encapsulated statistical data mining models and associated metadata called Predictive
Model Markup Language (PMML), and Stored in a scoring engine. New
data from any source is evaluated using models stored in the scoring engine [9].
A big data software stack for manufacturing analytics can be a mix of open source, commercial, and proprietary tools. An example of a
manufacturing analytics software stack is shown in Figure 2. It is known from completed projects that existing stack vendors do not currently
offer complete solutions. Although the technology landscape is evolving rapidly, the best option currently is modularity with a focus on truly distributed
components, with the core idea of success being a mix of open source and commercial components [10].
In addition to the architecture presented here, there are various commercial IoT platforms. These include GE”s Predix ( www.predix.com ), Bosch”s IoT
suite (www.bosch-iot-suite.com), IBM”s Bluemix ( www.ibm.com/cloud-computing/ ), ABB based on Microsoft Azure IoT services and people platform
and Amazon’s IoT cloud (https://aws.amazon.com/iot). These platforms offer many standard services for IoT and analytics, including identity management and data
security, which are not covered in the case study here. On the other hand, the best approaches offer flexibility and customizability, making implementation
more efficient than standard commercial solutions. But implementing such a solution may require a capable data science team at the implementation site.
The choice comes down to several factors, non-functional requirements, cost, IoT and analytics.
MDD112D-N030-N2M-130GA0
MHD041B-144-PG1-UN
MHD093C-058-PG1-AA
MKD025B-144-KG1-UN
MKD071B-061-KG0-KN
MKD071B-061-KP0-KN
MSK030C-0900-NN-M1-UP1-NSNN
MSK060C-0600-NN-M1-UP1-NSNN
MSK060C-0600-NN-S1-UP1-NNNN
MSK070C-0150-NN-S1-UG0-NNNN
MSK070D-0450-NN-M1-UP1-NSNN
REXROTH PIC-6115
REXROTH PSM01.1-FW
REXROTH R901273425A
REXROTH R900775346
REXROTH R901325866
REXROTH R901325866+R901273425A
REXROTH R900775346+R901273425A
R901325866+R900775346+R901273425A
REXROTH R911259395
REXROTH RAC 2.2-200-460-A00-W1
REXROTH SE110 0608830109
REXROTH SE200 0608830123
SL36 REXROTH
SYHNC100-NIB-2X/W-24-P-D-E23-A012
REXROTH TV 3000HT PUMF
VDP40.2BIN-G4-PS-NN
VT-HNC100-1-23/W-08-0-0 R900955334
REXROTH VT-VPCD-1-15/V0/1-P-1
REXROTH VT-VSPA2-1-10/T1 REXROTHPA1-1-11
REXROTH VT2000-52 R900033828
REXROTH VT3000S34-R5
REXROTH VT3002-2X/48F
REXROTH VT3006S34R5
REXROTH VT3006S35R1
REXROTH VT3024
ABB Tension sensor 3BSE008922R101
ABB PFTL 201DE-100.0 3BSE008922R101
ABB PFTL 201D-1000 3BSE008922R100
ABB Tension sensor 3BSE008922R100
ABB Tension sensor 3BSE008922R51
ABB PFTL 201DE-50.0 3BSE008922R51
ABB PFTL 201D-50.0 3BSE008922R50
ABB Tension sensor 3BSE008922R50
ABB PFTL 201CE-50.0 3BSE007913R51
ABB Tension sensor 3BSE007913R51
ABB Tension sensor 3BSE007913R50
ABB PFTL 201C-50.0 3BSE007913R50
ABB PFTL 201CE-20.0 3BSE007913R21
ABB Tension sensor 3BSE007913R21
ABB Tension sensor 3BSE007913R20
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