Description
hardware flow control. It is an ideal choice in the field of industrial automation.
3.2 Machine learning
As the functionality of distributed computing tools such as Spark MLLib (http://spark.apache.org/mllib) and SparkR (http://spark.apache
.org/docs/latest/index.html) increases, it becomes It is easier to implement distributed and online machine learning models, such as support
vector machines, gradient boosting trees and decision trees for large amounts of data. Test the impact of different machine parameters and process
measurements on overall product quality, from correlation analysis to analysis of variance and chi-square hypothesis testing to help determine the impact of individual
measurements on product quality. This design trains some classification and regression
models that can distinguish parts that pass quality control from parts that do not. The trained models can be used to infer decision rules. According to the highest purity rule,
purity is defined as Nb/N, where N is the number of products that satisfy the rule and Nb is the total number of defective or bad parts that satisfy the rule.
Although these models can identify linear and nonlinear relationships between variables, they do not represent causal relationships. Causality is critical to
determining the true root cause, using Bayesian causal models to infer causality across all data.
3.3 Visualization
A visualization platform for collecting big data is crucial. The main challenge faced by engineers is not having a clear and comprehensive overview of the complete manufacturing
process. Such an overview will help them make decisions and assess their status before any adverse events occur. Descriptive analytics uses tools such as
Tableau (www.tableau.com) and Microsoft BI (https://powerbi.microsoft.com/en-us) to help achieve this. Descriptive analysis includes many views such as
histograms, bivariate plots, and correlation plots. In addition to visual statistical descriptions,
a clear visual interface should be provided for all predictive models. All measurements affecting specific quality parameters can be visualized and the data
on the backend can be filtered by time.
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RS-FS-9001 362A1052P104 Flame detector
1769-L23E-QB1B CompactLogix 5370 L2 package controller
1747-ACNR15 SLC 500 I/O adapter module
1756-PA72 ControlLogix Standard power supply
1756-PA75 Power module
086349-002 Controller card module
086349-002 Controller card module ABB
086329-004 Frame module
1C31124G01 Analog Volume input card
CDIO 16/16-0,5-1131 BERGHOF servo drive
1768-L43 CompactLogix series industrial controller
TC-PRR021 Redundant module
TC-4000-P-PB-ES power driver
SAN4-40M DDK servo drive supporting controller
SR1030B62 YOKOGAWA AC servo motor DD motor
DR1030B60 YOKOGAWA Yokogawa AC servo motor
6410-009-N-N-N pulse encoder
IC200CHS022 Input/output carrier module
IC695PSA040J Power module
UP55A-020-11-00 Program controller
IC200PWR002 Power supply miniature
CE4003S2B9 16-channel dual-wire AI terminal board
VE4035S2B1 Redundant analog output card
3500/53-03-00 3500/53 Electronic speed detection system
FDPI-02 3AUA0000108650 Panel Bus adapter
IC695PSD040F Power module
RDCO-04C 68882915 DCS communication adapter
DI581-S 1SAP284000R0001 Digital input module
DX581-S 1SAP284100R0001 Digital input/Output module
TU582-S 1SAP281200R0001 I/O terminal device
TU516 1SAP212000R0001 I/O terminal Unit
DO524 1SAP240700R0001 Digital output module
HDS04.2-W200N-HT01-01-FW Drive controller
HDS04.2-W200N-HS32-01-FW Drive controller
HDS05.2-W300N-HT46-01-FW Drive controller
140NOC78000 Ethernet DIO network module
WS-C2960X-48TS-LL Ethernet switch
1756-OF6CI isolation analog output module
1783-ETAP Embedded switch
R88D-KT10F servo driver Omron
MPL-B890C-MJ74AA high quality permanent magnet rotating servo motor
2198-D032-ERS3 dual-axis Kinetix servo drive
1769-IF4XOF2 analog input/output combination module
1769-OF8V analog output module
AAI141-h00/K4A00 AAI141 Analog input module
330103-00-04-10-02-05 3300 XL 8mm short range probe
2093-AC05-MP5 Integrated shaft module
2198-D012-ERS3 dual-axis inverter
1756-OF8A analog output module
1756-IF8A Analog input module
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