6533b857fe1ef96bd12b39c3

RESEARCH PRODUCT

Quality Improvement Based on Big Data Analysis

Carmen SimionRadu Adrian CioraMarius Cioca

subject

Quality managementbusiness.industryComputer sciencemedia_common.quotation_subjectBig dataAutomotive industryLinked dataRecommender systemData modelingRisk analysis (engineering)Business intelligenceQuality (business)businessmedia_common

description

Big data analysis has become an important trend in computer science. Quality improvement is a constant in current industry trends. In this paper, we present an idea of quality improvement based on big data analysis with the aid of linked data and ontologies in order to implement it in the case of automotive parts production. We consider defective automotive products and try to find the best refurbishment solution for them considering their characteristics. Moreover, we propose to develop a recommender system that is able to give recommendations in order to prevent or to alleviate defects and to provide insights for possible causes that led to these defective parts. This study intends to help direct beneficiaries (public consumer, quality engineers, quality control managers), but also specialists and researchers in the NLP, software engineers, etc.

yearjournalcountryeditionlanguage
2016-01-01
https://doi.org/10.1007/978-3-319-32942-0_7