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Defect Classification in Factory with XGBoost

Introduction

This project aims to classify whether an item in a factory's production line is considered as a defect. The notebook contains thoughts and processes througout the project. Including the feature engineering, data understanding, motivations behind the methods used, handling the imbalanced class problem.

Dataset Description

  • Example of Product Name : I-B-XA1207672-190701-00494.
  • ID = PROX TRAZ = it's a unique code given to the product.
  • XA1207672 is the reference.
  • 190701 is the date: here 01st of July of year 2019.
  • 00494 is the unique code given to the product, whatever it happens, the product will have this id number frozen forever.
  • This number is increased by 1 each time we process a new product, every 12s. So for example : I-B-XA1207672-190701-00495 is the next product.
  • Inputs : Input features are measures collected on di�erent assembly stations with the sensors or devices connected to Programmable Logic Controllers which are storing all of them to keep the full quality traceability (Examples : OP070 V 1 angle value, OP120 Rodage I value, etc. . . ).
  • Output : This is the result value of OP130 (test bench). Value 0 is assigned to OK samples (passed) and value 1 is assigned to KO samples (failed). This is the combined result of multiple electrical, acoustic and vibro-acoustic tests.

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