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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IS200EISBH1A Exciter ISBus board
IS200EHPAG2D pulse amplifier module
IS200EHPAG1C excitation high voltage pulse amplifier
IS200EHPAG1D high voltage gate pulse amplifier
IS200EHPAG1B high voltage pulse amplifier board
IS200EHPAG1A pulse amplifier board
IS200EHFCH2A excitation fan control
IS200EHFCH1A exciter fan control board
IS200EGPAG1B Temperature monitoring module
IS200EGPAG1A Temperature monitoring module
IS200EGDMH1A Ground detection board
IS200EDSLH2A transmission control unit
IS200EDSLH1A dual voltage regulator
IS200EDFFH3A DC feedback board
IS200EDFFH2A excitation module
IS200EDFFH1A Interface board
IS200EDEXG2B degaussing module
IS200EDEXG2A exciter board
IS200EDEXG1A communication card
IS200EDEXG1B excitation module
IS200EDCFG1B I/O terminal board
IS200EDCFG1A DC feedback board
IS200ECTXG1A Exciter CT expansion board
IS200ECTBG1A Output and input modules
IS200ECTBG2A contact terminal board
IS200EBRGH2A Interface board
IS200EBRGH1A Excitation bridge interface board
IS200EBKPG1C Backplane control board
IS200EBKPG1B exciter backplane control board
IS200EBKPG1A Excitation control backplane
IS200EBACG1A Digital controller
IS200EAUXH1A digital controller
IS200EACFG3A feedback board
IS200EACFG3B exciter AC feedback board
IS200EACFG2B excitation control module
IS200EACFG2A actuator AC feedback board
IS200EACFG1B exciter module
IS200EACFG1A AC feedback board
IS200DSPXH2D processor control board
IS200DSPXH1D digital signal processor control board
IS200DSPXH1C processor controller
IS200DSPXH1B digital signal processor board
IS200DSPXH1A digital signal controller
DS2020DACAG2 EX2100 series power module
DS2020DACAG1 Power module
IS420YDOAS1B I/O Ethernet network
IS420YAICS1B simulates I/O
IS420UCSDH1A quad-core controller
IS420UCSCH1B Balance controller
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