manufacturing 1.1.22

Six-Sigma based analysis of manufacturing data

Purpose

To provide analysis tools and metrics useful in manufacturing environments.

Go to the documentation.

Project Maturity

Project is currently undergoing frequent updates for documentation and to add functionality and update documentation!! Screenshots and features that you see on here may be out of date, but are in progress.

Current focus is to add test coverage and shore up functionality that has been implemented. All versions before v1.2.0 will be minor bugfixes or minor functionality as it is revealed in test development.

Installation

To install from pypi:

pip install manufacturing

To install from source download and install using poetry:

poetry install

Usage

Cpk Visualization

The most useful feature of the manufacturing package is the visualization of Cpk. As hinted previously, the ppk_plot() function is the primary method for display of Cpk visual information. First, get your data into a list, numpy.array, or pandas.Series; then supply that data, along with the lower_control_limit and upper_control_limit into the ppk_plot() function.

manufacturing.ppk_plot(data, lower_specification_limit=-2, upper_specification_limit=2)

In this example, it appears that the manufacturing processes are not up to the task of making consistent product within the specified limits.

Zone Control Visualization

Another useful feature is the zone control visualization.

manufacturing.control_chart(data)

There are X-MR charts, Xbar-R charts, and Xbar-S charts available as well. If you call the control_chart() function, the appropriate sample size will be selected and data grouped as the dataset requires. However, if you wish to call a specific type of control chart, use

• x_mr_chart
• xbar_r_chart
• xbar_s_chart

Contributions

Contributions are welcome!

RoadMap

Items marked out were added most recently.

• ...
• Add use github actions for deployment
• Transition to poetry for releases
• Add I-MR Chart (see examples/imr_chart.py)
• Add Xbar-R Chart (subgroups between 2 and 10)
• Add Xbar-S Chart (subgroups of 11 or more)
• Update documentation to reflect recent API changes
• Add automated testing

Gallery