Quality data analysis using Python
Rajesh Sampathkumar (~rajesh8) |
The analysis of such data specific to product and process quality has so far been done using closed source applications (such as SAS, SPSS and Minitab), but the opening up of the Python based open source frameworks and libraries gives us an opportunity to analyze such data using Python and its various libraries. What's more, this opens up new avenues to use advanced machine learning and visualizations.
In this talk, I'll deal with some of the applications of the libraries, functions and approaches you find within Python's data science stack, and its application to the problem of analysing product and process quality data. Some aspects of the talk will be:
- Problem characterisation and definition using data analysis
- Data visualization and analysis for time series, continuous data and proportion data
- Process capability analysis with Python
- Control charts and SPC charts with Python
- Frequentist statistics in Python (significance testing, ANOVA)
- Failure mode analysis using text classfication
The target audience for this may or may not come in with some industrial experience in products, processes or quality management. They're however expected to know some Python and should be aware of some of the broad functionality within the Python data science stack.
Rajesh Sampathkumar is a consulting professional with around 13 years of experience, spanning manufacturing engineering, product design and development, quality management, 6 sigma and data science. He enjoys Python programming and working on the Python data science stack. At The Data Team, Rajesh's role as a senior consultant is to work with clients to help them get the best results, the best productivity and scale out of their data engineering and data science initiatives. Rajesh's other professional interests are aerospace and automotive engineering technologies.
The Data Team is a premier consulting company that provides expert consulting services in the areas of big data and data science. Founded by veterans in the big data and data science worlds, the company's portfolio of services include business strategy, IT roadmap & adoption, solution design, architectural leadership, data-related R&D, training and mentoring.
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