Avijit Biswas
Lean Optimization of newly established Assembly Line using Data Analysis of Quality by the feed from Image recognition Industry 4.0 and Jishuken Study.
Rel. Paolo Chiabert. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2021
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Abstract
Electric vehicles are emerging and evolving with time future-oriented tend to more automation and data-oriented results which is more near to the accuracy. This leads to taking fast decision-making. Covid -19 pandemic accelerated automation further which is a part of Industry 4.0. with the growing trend of connecting different sectors of industries among each other all activities are associated with both Value Addition (VA) and Non-Value Addition (NVA) traits. A lean approach can be adopted in order to reduce NVA through waste reduction. Where the data are being collected from the assembly line from operations which automatic or manually performed. The thesis proposes a technique focusing on optimizing a newly established Assembly line eliminating wastes and quality defects to improve the OEE (overall equipment effectiveness).
Data collected by MES (Manufacturing Execution System) through Images with pattern recognition and process deviation
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