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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ACSM1-04AM-016A-4 Mechanical drive module
1756-CNBR/E Communication interface module
3HAC025338-004/06D main servo drive unit
1747-L552/C SLC 500 processor
3HAC7998-2 Cable
IS200ERRRH1A Redundant relay for exciter regulator
2711P-T10C15D1 Operator terminal
2711P-T10C15D1 Operator terminal
2711P-T10C15A1 Operator terminal
2711P-T7C15D1 Touch screen
UFC719AE101 3BHB003041R0101 Controller module
UGTMEM-03LBB11 22.5V servo motor
20BD8P0A3AYNAND0 Digital PWM AC driver
6FC5203-0AF02-0AA1 Siemens Operating panel
HE693SNP306AX Cable connector
QTERM-K65 Beijer panel installation man-machine interface
2711PC-T6C20D8 PanelView Plus 6 Compact 600 Graphics terminal
CIMREX60 BEIJER Operator Panel
NTCF23 Optical fiber communication terminal
F3322 Digital output module
F7133 4-channel power distribution module
6181P-15TP2KH integrated display computer
IS220PSVOH1A servo control package
8440-1715 SPM-D11 synchronizer WOODWARD
FC-TSAI-1620M Security manager system module
TSXP57204M SCHNEIDER Processeur TSX 57
IMDSO04 Digital slave output module
P0926JM FOXBORO Secondary power input
330851-02-000-060-10-00-00 Expansion sensor
330850-50-00 BENTLY NEVADA preprocessor
330854-040-24-00 Differential extension cable
1746-NIO4V Analog Input
1785-V40L Programmable controller
TRICONEX 3720 Communication Module 3721 3721C
PFTL101B 2.0KN 3BSE004185R1 Tension sensor
DS200SIOBH1ACA circuit board module
UTV-F2500HA Manipulator controller
6DD1661-0AB1 Communication component
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