Litcius/Paper detail

A Survey on Machine Learning based Smart Maintenance and Quality Control Solutions

Attila Frankó, Pál Varga

2021Híradástechnika/Infocommunications journal16 citationsDOIOpen Access PDF

Abstract

Machine learning aided tasks and processes have key roles in smart manufacturing, especially in controlling production and assembly lines, as well as smart maintenance and intelligent quality control. The last two ones are those tasks that nowadays are still performed manually by employees; however, there are numerous machine learning-based solutions that can automate these fields to optimize cost and performance. In this paper, we present an overview of smart manufacturing ecosystem and define the roles of maintenance and quality control in it. Up-to-date machine learning-based smart solutions will also be detailed while addressing current challenges and identifying hot research topics and possible gaps.

Topics & Concepts

Control (management)Computer scienceQuality (philosophy)Key (lock)Smart manufacturingProduction (economics)Manufacturing engineeringProcess managementEngineering managementArtificial intelligenceEngineeringComputer securityMacroeconomicsPhilosophyEpistemologyEconomicsDigital Transformation in IndustryIndustrial Vision Systems and Defect DetectionManufacturing Process and Optimization