3BIE010749 DCS excitation system

Product parameters

Model: 3BIE010749

Brand: ABB

Size: 10cm x 10cm x 30cm

Weight: 1.2KG

Color: White Black

Working voltage: 5V

Working temperature: -10 ℃ to 50 ℃

Communication interface: RS232, RS485, CAN

Product specifications

Support for MODBUS protocol

Support hardware flow control

Using high-speed CMOS devices

Support for data caching

application area

3BIE010749 is mainly used in the field of industrial automation, such as DCS PLCs, industrial controllers, robots, etc.

3BIE010749 is mainly used in steel manufacturing, thermal power generation, hydroelectric power generation, glass manufacturing, paper mills, cement factories, petrochemicals

Chemical fiber, pharmaceutical manufacturing, rubber, plastics, ferrous metal food, machine tools, specialized equipment, transportation vehicles, mechanical equipment

Electronic communication equipment, instruments and beverages, tobacco processing, clothing, textiles, leather, wood processing, furniture, printing, etc

Model: 3BIE010749 Brand: ABB Archive Function: Communication Function Product Certification: Qualified

Working voltage: 24V Internal variable: No pattern Type: Vector diagram Applicable range: Industrial type

Number of screens: 4 Imported or not: Yes Customized for processing: No

Alarm function: Product name: Module Input voltage: 24V Rated current: 5A

Special service: including postage. Remarks: one-year warranty. Operation method: remote control

Applicable motor: servo motor system memory: 8MB Display color: 99.9 color gamut

Power voltage: 220V Input method: Current Input Material code: 65218

Communication interface: HDMI interface Working temperature: 60 Material number 26854 Other functions Analog communication

Output frequency: 50HZ Rated voltage: 24V Alarm type: Light alarm

Disconnect capacity: 0.01 Vector graph support: Minimum number of packages supported: 1

Display type: IPS USB interface quantity: 2 interfaces Memory card slot: 2

Panel protection level: 3 Memory expansion capacity: 128MB User script support: supported

Speed response frequency: 1MS Working environment temperature: -40 to 100 Insulation withstand voltage test: Passed

Third party communication products: ABB controllers available for sale in: nationwide

Product Instructions

Please install 3BIE010749 correctly on the device and connect the communication interface cable properly.

Please refer to the user manual for operating 3BIE010749 to ensure proper use.

Product Introduction

3BIE010749 is a high-performance industrial automation communication module that uses high-speed CMOS devices, supports MODBUS protocol, and supports
hardware flow control. It is an ideal choice in the field of industrial automation.

(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.

1769-L32E  Allen-Bradley Programmable automation controller
1769-L30ERMS Allen-Bradley CompactGuardLogix controller
1769-L24ER-QBFC1B  CompactLogix 5370 L2  controller
1769-IT6  Thermocouple / milivolt Input Module
1769-IF8 Compact I/O analog input module
1769-IA16  Allen-Bradley  16 Channel Input Module
1769-ADN DeviceNet communication module
1762-L40BWAR Programmable Logic Controller (PLC)
1762-IF4  Differential channels analog input module
1757-SRM  ControlLogix System Redundancy Module
1756-TBNH  removable terminal block or RTB module
1756-RMB  ControlLogix Redundancy module
1756-RM redundant module
1756-OF8 analog output module
1756-PA75RA  ControlLogix Redundant Power Supply
1756-OF4  ControlLogix Four (4) channel analog output module
1756-OB32 ControlLogix Discrete output module
1756-L542 Allen-Bradley  SLC 5/03 controller
1756-L75  Allen-Bradley  ControlLogix Controller
1756-L71S Programmable controller
1756-L71 ControlLogix Logix5571 processor module
1756-L61  ControlLogix controller
1756-IF8H  ControlLogix I/O module
1756-IB32 Input module
1756-IB16 I/O module
1756-ENBT Optical fiber interface board module
1756-EN2TXT Ethernet /IP module
1756-EN2TR Communication module
1756-EN2TEthernet /IP module
1756-DNB Scanner module
1756-DHRIO Programmable controlle
1756-BATM Programmable logic controller
1756-A13 chassis
1755T-PMPP-1700 Touch screen
1755-A6 module
1747-SDN Communication module
1747-KE Communication module
1747-FC Input/output module
1747-DCM Input/output module
1747-C10 driver
1747-ACNR15 Processor module
1746-P4 Power module
1746-OV8 Programmable controller
1746-OB16E  Allen-Bradley  Programmable controller
1746-OA8 Programmable controller
1746-IV32 Allen-Bradley  SLC 500 Discrete Input module
1746-A2 Programmable logic control