Gorkem SariyerSachin Kumar Kumar ManglaYigit KazancogluCeren Ocal TasarSunil LuthraSariyer, GorkemTasar, Ceren OcalLuthra, SunilMangla, Sachin KumarKazancoglu, YigitOcal Tasar, Ceren2025-10-06202515729338, 025453300254-53301572-933810.1007/s10479-021-04215-92-s2.0-85112624139https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112624139&doi=10.1007%2Fs10479-021-04215-9&partnerID=40&md5=31b477e2f8f0e042df440930fe6ca1dehttps://gcris.yasar.edu.tr/handle/123456789/7989https://doi.org/10.1007/s10479-021-04215-9Advances in smart technologies (Industry 4.0) assist managers of Micro Small and Medium Enterprises (MSME) to control quality in manufacturing using sophisticated data-driven techniques. This study presents a 3-stage model that classifies products depending on defects (defects or non-defects) and defect type according to their levels. This article seeks to detect potential errors to ensure superior quality through machine learning and data mining. The proposed model is tested in a medium enterprise—a kitchenware company in Turkey. Using the main features of data set product customer country production line production volume sample quantity and defect code a Multilayer Perceptron algorithm for product quality level classification was developed with 96% accuracy. Once a defect is detected an estimation is made of how many re-works are required. Thus considering the attributes of product production line production volume sample quantity and product quality level a Multilayer Perceptron algorithm for re-work quantity prediction model was developed with 98% performance. From the findings re-work quantity has the highest relation with product quality level where re-work quantities were higher for major defects compared to minor/moderate defects. Finally this work explores the root causes of defects considering production line and product quality level through association rule mining. The top mined rule achieves a confidence level of 80% where assembly and material were identified as main root causes. © 2025 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessAssociation Rule Mining, Data Analytics, Industry 4.0, Machine Learning, Manufacturing, Msme, Quality Control, Re-work And Root Causes Of DefectRe-Work and Root Causes of Defect0Data AnalyticsQuality ControlIndustry 4.0ManufacturingIndustry 4Machine LearningMSMEAssociation Rule MiningArticle