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About lss-kruskal-wallis

Lean Six Sigma with Python — Kruskal Wallis Test

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Web Self-hosted

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Python

Lean Six Sigma with Python — Kruskal Wallis Test 👷

How to replace Minitab with Python to perform the Kruskal-Wallis Test, evaluating the impact of training on warehouse operators’ productivity

Lean Six Sigma (LSS) is a method based on a stepwise approach to process improvements. This approach usually follows five steps. (Define, Measure, Analyse, Improve and Control) for improving existing process problems with unknown causes.

Youtube Video

Find in the link below a short animated video to explain the concept behind this solution

Explainer Video Link

Article

In this Article, we will explore how Python can Replace Minitab (Software widely used by LSS experts) in the Analysis step to test hypotheses and understand what could improve the performance metrics of a specific process.

Scenario

You are the Continuous Improvement Manager of a Distribution Centre (DC) for an iconic Luxury Maison focusing on Fashion, Fragrances and Watches. The warehouse receives garments that require final assembling and value-added service (VAS) during the inbound process.

Objective

With support from the R&D team, you designed training for VAS operators to improve productivity and reduce quality issues.

Question

Does the training have a positive impact on operator productivity?

Hypothesis

The training has a positive effect on VAS operators' productivity.

Experiment

Randomly select operators and measure the time per batch (Time to finish a batch of 30 labels in seconds) to build a sample of 56 records.

Code

In this repository, you will find all the code used to explain the concepts presented in the article.

Files

  • Kruskal Wallis Test.ipynb - Jupyter notebook with step-by-step analysis
  • kruskal_wallis_test.py - Standalone Python script
  • data/ - Folder containing input data (df_sewing.xlsx)

Getting Started

pip install -r requirements.txt
python kruskal_wallis_test.py

Dependencies

  • pandas
  • numpy
  • matplotlib
  • seaborn
  • scipy
  • pingouin
  • bioinfokit
  • statsmodels
  • openpyxl

About me 🤓

Senior Supply Chain and Data Science consultant with international experience working on Logistics and Transportation operations. \ For consulting or advising on analytics and sustainable supply chain transformation, feel free to contact me via Logigreen Consulting. \

Please have a look at my personal blog: Personal Website