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Reliability in the Age
of Big Data
TNO - Jan Eite Bullema | ASQ CQE, ASQ CSSBB
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Reliability in the Age of Big DATA
The nature of Big Data: new types of dataOpportunities of Big Data for Reliability: new reliability methods
New degradation models and application of Digital TwinsNew types of covariatesApplication of Machine Learning
Emergence of new reliability applicationsNew propositions: use based insurance, early warning warranty
Zhang & Meeker, Big Data and Reliability Applications, 2018 3
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The nature of Big Data: Many V’s
Many V’s (Variety, Volume, Veracity, Velocity, Value, Variability, Visualise)brontobyte (1027) = 1000 yottabyte (1024) = 1000000 zettabyte (1021)
Big Data has often complex structures or is even totally unstructuredhigh speed sensor data, video, images, text, weather, environment, Email
Emergence of (Industrial) Internet of Things2015: 15 billion iot sensors/devices 2025: 75 billion iot sensors/devices
https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/ 4
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Big data in Semicon ManufacturingExplosion in Generated Data
20041 FAB produces 1 Terabyte/day
20141 FAB produces 1 Petabyte/day
20201 FAB
multiple Petabytes/day
http://electroiq.com/blog/2014/09/the-semiconductor-industry-out-in-front-but-lagging-behind 5
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Twin-engine aircraft with 12-hr. flight-time can produce up to 844 TB of data
http://aviationweek.com/connected-aerospace/internet-aircraft-things-industry-set-be-transformed 6
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Value Creation in Industry 4.0
Most value creation in implementation of Industry 4.0 will occur not by replacing equipment as in previous industrial revolutions, but by equipping existing equipment with sensors so that machines can be used more efficiently and productively
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The nature of Big Data: new data typesMulti variate time series date: e.g. high speed multi-channel sensor data
Functional Data: e.g. functional curves, e.g. data from spectrometers
Image Data / Video Streams: e.g. camera image data or electron microscope image data
Unstructured: e.g. text, audio
Zhang & Meeker, Big Data and Reliability Applications, 2018 8
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Example of New Data Types: images and Video Streams for defect classification
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Example of New Data Types: images and Video Streams for defect classification
9https://aws.amazon.com/mxnet/
Deep Learning Model
Training the Model
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Example of New Data TypesText Mining
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Digital twin
12https://www.capgemini.com/2018/08/digital-twin-physical-meets-digital-world/
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Digital twin
13https://www.capgemini.com/2018/08/digital-twin-physical-meets-digital-world/
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Predictive Maintenance: Improved Asset Utilization
Case: Deposition Tool
Applied Materials claims that a customer increased profits > $100,000 per chamber, per year using predictive maintenance modelling
Charlie Pappis, Optimizing Fab Through Data Analytics, Nano chip Fab Solutions, V9/ Issue 2/2014 14
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Predictive Maintenance: Improved Asset Utilization
Jan Eite Bullema, How to make Big Data Productive in Semiconductor Manufacturing, 2016 15
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Predictive Maintenance: Improved Asset Utilization
Jan Eite Bullema, How to make Big Data Productive in Semiconductor Manufacturing, 2016
After a serious manufacturing Issue, control charts for deposition were adapted with a general model for sputtering Voltage
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Predictive Maintenance: Improved Asset Utilization
Jan Eite Bullema, How to make Big Data Productive in Semiconductor Manufacturing, 2016
A new model was developed that predicts sputtering Voltage for 18 machines and 40 recipes
This model is 6 times better than the previous Voltage prediction model
The model gives additional information about machine status
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Predictive Maintenance: Improved Asset Utilization
Jan Eite Bullema, How to make Big Data Productive in Semiconductor Manufacturing, 2016 17
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CONCLUSION
Big Data technology leads to new types of data high dimensional sensor data, images, functional curves, text messages
That lead to new statistical methods in reliability functional data analysis, text mining, deep learning and image regression
That lead to higher levels of reliability and new propositionsuse based insurance, use based warranty
Zhang & Meeker, Big Data and Reliability Applications, 2018 19
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Thank You for your Attention
Reliability in the Age of Big Data
TNO - Jan Eite Bullema | ASQ CQE, ASQ CSSBB
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Jan Eite Bullema
• Bedrijfsnaam: TNO
• Adres: De Lismortel 31
• Telefoonnummer: 0888665551 / 0622800854
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