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Selecting Key Product Characteristics to Improve the QMS in Automotive Sector

EasyChair Preprint no. 7822

7 pagesDate: April 21, 2022


In the automotive industry, one of the major factors contributing to customer satisfaction is the product’s quality.
To improve this latter, companies are implementing quality management systems: QMS, which are requiring usage of quality tools especially statistical ones, to control the manufacturing processes, by monitoring the product’s characteristics. But, must we track all the characteristics to achieve the product compliance and system efficiency? This paper aims to give a solution model that will allow the organizations to select the key product characteristics that should be monitored by quality tools as they have the most influence on the product’s quality.
The goal is to use mathematics in industrial field to improve quality management systems and manufacturing processes performances.
The paper also gives architecture of the discussed problematic and a perspective on the next work which will be an application of the proposed solution in the automotive sector.

Keyphrases: automotive industry, Data Mining, linear regression, machine learning, Product characteristics identification, Quality Improvement

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Laila Benzaza and Najlae Alfatehi and Abdelouahid Lyhyaoui},
  title = {Selecting Key Product Characteristics to Improve the QMS in Automotive Sector},
  howpublished = {EasyChair Preprint no. 7822},

  year = {EasyChair, 2022}}
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