Description
hardware flow control. It is an ideal choice in the field of industrial automation.
3 Case Studies on Reducing Scrap Rates
Any product assembled or produced in a factory goes through a series of quality tests to determine whether it needs to be scrapped.
High scrap rates are caused by the opportunity cost of not delivering products to customers in a timely manner, wasted personnel time, wasted
non-reusable parts, and equipment overhead expenses. Reducing scrap rates is one of the main issues manufacturers need to address. Ways to
reduce scrap include identifying the root causes of low product quality.
3.1 Data processing
Root cause analysis begins by integrating all available data on the production line. Assembly lines, workstations, and machines make up the industrial
production unit and can be considered equivalent to IoT sensor networks. During the manufacturing process, information about process status,
machine status, tools and components is constantly transferred and stored. The volume, scale, and frequency of factory production considered in
this case study necessitated the use of a big data tool stack similar to the one shown in Figure 2 for streaming, storing, preprocessing, and
connecting data. This data pipeline helps build machine learning models on batch historical data and streaming real-time data. While batch
data analytics helps identify issues in the manufacturing process, streaming data analytics gives factory engineers regular access to the latest
issues and their root causes. Use Kafka (https://kafka.apache.org) and Spark streaming (http://spark.apache.org/streaming) to transmit real-time
data from different data sources; use Hadoo (http://hadoop.apache.org ) and HBase (https://hbase.apache.org) to store data efficiently; use
Spark (http://spark.apache.org) and MapReduce framework to analyze data. The two main reasons to use these tools are their availability as open
source products, and their large and active developer network through which these tools are constantly updated.
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SCXI-1302 NI Feed-Through Terminal Block
MMS6312 EPRO Machinery Health Monitor
1C31203G01 Westinghouse Remote Node Controller
1900/65A-01-01-01-00-00 Bently Nevada General Purpose Equipment Monitor
TE 1605341 VER02 1605340-05 TRUMPF
CC12403 1021621 FSC
CC22103 1010621 FCS
REF615C-D HCFCACABANB2BAN1XD ABB PROTECTION AND CONTROL RELAY
07KR51 1SBP260011R1001 ABB programmable controller
FI820F 3BDH000031R1 ABB Fieldbus Module Serial
SLS1508 KJ2201X1-BA1 12P3162X212 Emerson Smart Logic Solver
SD812F 3BDH000014R1 ABB Power Supply
1746-OB32 Allen-Bradley SLC 500 Digital DC Output Module
140SAI94000S Schneider 8 INPUT ANALOG SAFETY INPUT MODULE
IC3645LXCD1TT GE CONTROLLER
BCU-12 3AUA0000110430 ABB Control unit
AI3351 TRICONEX Analog Input Card Module
BCU-02 3AUA0000110429 ABB Control unit
8311N TRICONEX Power Supply High Density Module
6410-024-N-N-N Pacific Scientific Drives-DC Servo
05701-A-0502 HONEYWELL Frame equipment
05701-A-0329 HONEYWELL Card module
1756-IF16 Allen-Bradley ControlLogix module
PP835 3BSE042234R1 ABB Operator Panel
320-1026C SBS PC BOARD
Y-3023-2-H00AA Allen-Bradley Brushless Servo Motor
GF1-10TVD-100 MICRO INNOVATION TOUCH PANEL
07AC91 GJR5252300R0101 ABB Analog I/O module
502476L KCEU14201F51PEB ALSTOM
1794-ASB Allen-Bradley FLEX Remote I/O Adapter 24VDC PS 8 I/O Module Capacity
1756-EN2TXT Allen-Bradley High Performance Bridge w/ Embedded Switch
TC-CCR014 97197975-A01 HONEYWELL REDUNDANT NET INTERFACE
VIPC616 91611524 0360-1152D SBS IndustryPack Carrier
OKYM175W22 ABB With battery contactor
J592S-450550 Dual Serial Port I/O Card
IOB-80 NYQUIST SERVO DRIVE I/O BOARD
NW-BM85C002 Schneider BM85 BRIDGE MULTIPLEXOR
IC754VSF12CTD Allen-Bradley Quick Panel Control
FBM215 P0917TQ FOXBORO Output Module
DSQC604 3HAC12928-1 ABB Power Supply
IC754VSI12CTD Allen-Bradley Human Machine Interface (HMI)
A201SR04 01A201S12 5880-0009 MAN CARRIER BOARD
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