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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VMIVME-7807 GE Pentium® M processor
SCXI-1124 NI Analog Output Module
SCXI-1100 NI Voltage Input Module for SCXI
PXI-8423 NI Isolated 2-Port RS485 Interface for PXI
PF3S-PSA2 IDEC POWER SUPPLY MODULE
PCIE-5565-PIORC PCI Express (PCIe) Reflective Memory (RFM) Node Interface Card
MVME6100 MOTOROLA VME Single Board Computer
DS200ADGIH1AAA GE AuxilIary Interface Board
5X00062G01 EMERSON HART Analog Output Module
3500/22M Bently Nevada Standard Transient Data Interface
VME-IP-Carrier VIPC616 91611524 SBS IndustryPack Carrier
3721C TRICONEX Analog Input Module
PLM 3900N TRICONEX
CB06560 PRD-B040SAIB-62 KOLLMORGEN Servo driver
FBM227 P0927AC FOXBORO 4 input and 2 output of module
1756-CNB Allen-Bradley communication adapter
SPS5710-2-LF 51198685-100 HONEYWELL POWER SUPPLY MODULE
SPS5710 51199929-100 HONEYWELL TDI POWER SUPPLY
SCYC51040 58052680E ABB Trigger plate
SCYC51090 58053899E ABB Trigger plate
PP886H 3BSE069297R1 ABB Rugged Touch Panel 15″
CI867 3BSE043661R1 ABB MODBUS TCP
IC695CRU320CA-EL GE PACSystems RX3i Redundancy CPU
UT150-1 ALSTOM
LE109A-1 ALSTOM
LC105A-1 ALSTOM
IR139-1 ALSTOM
AM164 ALSTOM
AL132 ALSTOM
AH116-2 ALSTOM
AB121 ALSTOM
YNT511D YASKAWA repeater
TPMC815-50 TEWS ARCNET Interface Module
PW501 YASKAWA
IS215UCVEM09A GE Industrial controller
CI854A-eA 3BSE030221R2 ABB PROFIBUS-DP/V1 interface
AIP578 YASKAWA Electrical Tranceiver RIO I/O Module
JZNC-XIU01B YASKAWA SERVO DRIVE
CC-IP0101 Honeywell Fieldbus Module
1336-L4 Allen-Bradley Motor controller
1336F-MCB-SP2G Allen-Bradley spare part main control board
DSRF182AK02 3BSE014078R1 ABB Expand input and output rack
PXIE-8840QC NI Embedded controller
ISH100/30025/0/0/00/0/00/01/00 ELAU actuating motor
K9202 996920202 HIMA T4 Cabinet Fan Module
MODHUB-16E CONTEMPORARY CONTROL MODULE
MX-CS101-701-G1 IMS Microstepping Motor Driver
P0926KP FOXBORO electric cable
RF533 3BSE014227R1 ABB Subrack 12SU Including Backplane
TG-13(8516-038)WOODWARD Mechanical-hydraulic governor of steam turbine
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