Beitragsseiten

Kapitel 6

Process Mining

Interview – Process Mining ist ein wichtiger Treiber der Prozessautomatisierung https://data-science-blog.com/blog/2017/10/19/interview-prof-scheer-process-mining-automation/ 
Celonis https://www.celonis.com/de/
Fluxicon https://fluxicon.com/disco/
Process Mining http://www.processmining.org/tools/start
Dataset - Production Analysis with Process Mining Technology https://data.4tu.nl/repository/uuid:68726926-5ac5-4fab-b873-ee76ea412399
ProM Tools http://www.promtools.org/doku.php
Online Course: Introduction to Process Mining with ProM https://www.futurelearn.com/courses/process-mining
Alpha Miner https://www.futurelearn.com/courses/process-mining/0/steps/15637
Fuzzy Miner (aktualisiert) http://processmining.org/online/fuzzyminer

 

Berichte

Data.gov - Consumer Complaint Database https://catalog.data.gov/dataset/consumer-complaint-database
German Stopwords https://github.com/solariz/german_stopwords/blob/master/german_stopwords_full.txt
nltk.stem package http://www.nltk.org/api/nltk.stem.html
German stemming algorithm http://snowball.tartarus.org/algorithms/german/stemmer.html
Stemming and Lemmatization with Python NLTK http://text-processing.com/demo/stem/
corpus: Text Corpus Analysis https://cran.r-project.org/web/packages/corpus/
ScitKit Learn - Logistic Regression  http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
ScitKit Learn - Working with data https://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html
Machine Learning, NLP: Text Classification using scikit-learn, python and NLTK. https://towardsdatascience.com/machine-learning-nlp-text-classification-using-scikit-learn-python-and-nltk-c52b92a7c73a

 

Wartung

automotiveIT: Predictive Maintenance enttäuscht Erwartungen https://www.automotiveit.eu/predictive-maintenance-enttaeuscht-erwartungen/news/id-0060652 
automotiveIT: Predictive Maintenance fristet Schattendasein https://www.automotiveit.eu/predictive-maintenance-fristet-schattendasein/news/id-0060169
Industrie 4.0 Index: Predicitive Maintenance bleibt noch deutlich hinter den Erwartungen https://www.staufen.ag/de/unternehmen/news-events/news/newsdetail/2018/02/industrie-40-index-predictive-maintenance-bleibt-noch-deutlich-hinter-den-erwartungen/
6.Turbofan Engine Degradation Simulation Data Set https://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/#turbofan
Modular Aero-Propulsion System Simulations - MAPSS, C-MAPSS, C-MAPSS40k https://www.grc.nasa.gov/www/cdtb/software/mapss.html
Getting Started with Predictive Maintenance Models https://www.svds.com/getting-started-predictive-maintenance-models/
Predictive Maintenance for IoT https://www.svds.com/predictive-maintenance-iot/
Data analysis and processing techniques for
remaining useful life estimations
https://rdw.rowan.edu/cgi/viewcontent.cgi?article=3433&context=etd
GitHub - Apache Spark - Turbofan Engine Degradation Simulation Data Set example in Apache Spark https://github.com/oluies/tedsds

 

Transporte

Bureau Of Transportation Statistics: Freight Analysis Framework  https://www.bts.gov/faf
Seaborn: statistical data visualization https://seaborn.pydata.org/
Geopy https://geopy.readthedocs.io/en/stable/
Great Circle Maps for Python https://github.com/paulgb/gcmap