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086339-001 simulation module

Original price was: $1,888.00.Current price is: $1,688.00.

Model:086339-001

New original warranty for one year

Brand: ABB

Contact person: Mr. Lai

WeChat:17750010683

WhatsApp:+86 17750010683

Email: 3221366881@qq.com

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Description

Product parameters
Model: 086339-001
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
086339-001 is mainly used in the field of industrial automation, such as DCS PLCs, industrial controllers, robots, etc.
086339-001 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: 086339-001 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 086339-001 correctly on the device and connect the communication interface cable properly.
Please refer to the user manual for operating 086339-001 to ensure proper use.
Product Introduction
086339-001 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.

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.

Contact person: Mr. Lai
Mobil:17750010683
WeChat:17750010683
WhatsApp:+86 17750010683
Email: 3221366881@qq.com

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