Description
129740-102 Модуль ввода / вывода ABB
(5) Perform predictive maintenance, analyze machine operating conditions, determine the main
causes of failures, and predict component failures to avoid unplanned downtime.
Traditional quality improvement programs include Six Sigma, Deming Cycle, Total Quality Management (TQM), and Dorian Scheinin’s
Statistical Engineering (SE) [6]. Methods developed in the 1980s and 1990s are typically applied to small amounts
of data and find univariate relationships between participating factors. The use of the MapReduce paradigm to simplify data processing in
large data sets and its further development have led to the mainstream proliferation of big data analytics [7]. Along with the development of
machine learning technology, the development of big data analytics has provided a series of new tools that can be applied to manufacturing
analysis. These capabilities include the ability to analyze gigabytes of data in batch and streaming modes, the ability to find complex multivariate
nonlinear relationships among many variables, and machine learning algorithms that separate causation from correlation.
Millions of parts are produced on production lines, and data on thousands of process and quality measurements are collected for them, which is
important for improving quality and reducing costs. Design of experiments (DoE), which repeatedly explores thousands of causes through
controlled experiments, is often too time-consuming and costly. Manufacturing experts rely on their domain knowledge to detect key
factors that may affect quality and then run
DoEs based on these factors. Advances in big data analytics and machine learning enable the detection of critical factors that effectively
impact quality and yield. This, combined with domain knowledge, enables rapid detection of root causes of failures. However,
there are some unique data science challenges in manufacturing.
(1) Unequal costs of false alarms and false negatives. When calculating accuracy, it must be recognized that false alarms
and false negatives may have unequal costs. Suppose a false negative is a bad part/instance that was wrongly predicted to
be good. Additionally, assume that a false alarm is a good part that was incorrectly predicted as bad. Assuming further that
the parts produced are safety critical, incorrectly predicting that bad parts are good (false negatives) can put human lives
at risk. Therefore, false negatives can be much more costly than false alarms. This trade-off needs to be considered when
translating business goals into technical goals and candidate evaluation methods.
1734-RTB input/output module
1732E-OB16M12DR Expansion substrate
1492-SPM1C630 A-B Parameter measuring unit
1420-V2P-ENT PowerMonitor 500 AC power
1394-AM04 Allen-Bradley ControlLogix controller
1391-DES45 servo controller driver
1336-WB110 1336 series drive
1336-TR-SP1A programmable power board
1336-SN-SP6A inverter buffer board
1336-PB-SP2B DC power supply board
1336-MOD-L2 Logical interface board
1336-L5 Control interface board
1336F-BRF50-AA-EN-HAS2 Variable frequency driver
1336F-BRF15-AA-EN Variable frequency AC driver
1336F-B200-AA-EN-L4 Variable frequency AC driver
1336-BDB-SP53C Programmable logic controller
1336-BDB-SP37C controller
1336-B025-AA-EN-GM1 Frequency changer
1326AB-B720E-21 Servo motor
1203-GK5 Communication module
900G32-0001 Input module
853-049542-173 Servo driver Yes
836T-T254J Air compressor
810-800081-022 Control equipment
810-102361-222 LAM Research
810-073479-215 Semiconductor equipment
810-066590-004 Data acquisition board
810-046015-010 Foxboro VPN device
810-017034-005 Power strip
810-001489-016 Semiconductor PCB
567LH-DP24 Digital driver module
531X102CCHAFM2 Auxiliary plate
531X102CCHAEM1 Auxiliary plate
531X100CCHBCG1 Control panel
531X100CCHARM1 Control panel
531X100CCHAPM1 Control panel
531X305NTBAPG1 End plate
531X304IBDARG1 Base driver card
531X303MCPBBG1 Power circuit board
531X303MCPARG1 Ac power supply board
503-26606-21 Motion controller
490NRP95400 Fiber optic repeater
469-P1-HI-A20-E Analog output
440R-W23222 Safety relay switch
416NHM30030A High performance processor
269PLUS-DO-315-100P-HI
269PLUS-DO-311-100P-HI GE Multilin
269PLUS-DO-271-100P-120 Relay system
269PLUS-DO-225-100P-HI-125VDC Relay system
269PLUS-DO-212-10C-120 GE Multilin
269PLUS-DO-211-120N-120VAC Relay
269PLUS-DO-211-100P-120VAC Motor relay system
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