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Tackling the Problem of Defective Components in the Learning Factory Assembly Process by Using the Intelligent Assembly Line (CROSBI ID 704561)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Mladineo, Marko ; Gjeldum, Nikola ; Crnjac Zizic, Marina ; Aljinovic, Amanda ; Basic, Andrej ; Bilic, Bozenko ; Veza, Ivica Tackling the Problem of Defective Components in the Learning Factory Assembly Process by Using the Intelligent Assembly Line // SSRN Electronic Journal - Proceedings of the Conference on Learning Factories (CLF) 2021. Elsevier, 2021. str. 1-3 doi: 10.2139/ssrn.3858428

Podaci o odgovornosti

Mladineo, Marko ; Gjeldum, Nikola ; Crnjac Zizic, Marina ; Aljinovic, Amanda ; Basic, Andrej ; Bilic, Bozenko ; Veza, Ivica

engleski

Tackling the Problem of Defective Components in the Learning Factory Assembly Process by Using the Intelligent Assembly Line

The 4th industrial revolution, also known as Industry 4.0, is forcing enormous changes in technology and organization of the production. However, all these changes – faster and efficient production, higher product complexity, and broadening of the product varieties – can also lead to reduction of the quality. In terms of production, the reduction of the quality usually means increasing of the number of defective components, which leads to defective assemblies and final products. The industrial average for the automotive industry is more than 100 defects per 100 new cars. It sounds like a statistical paradox, but it is a reality of today’s automotive industry. It raises a question: why the technological advance doesn’t automatically bring the higher quality? The reason is that the final products are getting more complex with more components in the assemblies, and it results with a higher probability of the occurrence of the defects. In this research, an example of the gearbox assembly in Lean Learning Factory at University of Split is analyzed. The gearbox represents a complex assembly. First, it consists of many parts which need to be properly arranged, and secondly, the majority of parts have high accuracy geometric dimensions with fine tolerances. Such complexity increases the possibility of the defective final product. In this research, the methodology for probability calculation of defect occurrence is used to analyze the yield of the assembly process. Furthermore, an intelligent assembly line has been developing: workstations equipped with tablets for working instructions, RFID system for product tracking, etc. These intelligent elements improve the process quality by guiding worker step-by-step during the assembly process, and by fast analysis of defects root by using product tracking. The intelligent assembly line has been developed within the Learning Factory, so this knowledge can be passed to future engineers.

Assembly ; Quality ; Defect rate ; Learning Factory ; Industry 4.0

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Podaci o prilogu

1-3.

2021.

objavljeno

10.2139/ssrn.3858428

Podaci o matičnoj publikaciji

SSRN Electronic Journal - Proceedings of the Conference on Learning Factories (CLF) 2021

Elsevier

1556-5068

Podaci o skupu

11th Conference on Learning Factories (CLF 2021)

poster

01.07.2021-02.07.2021

Graz, Austrija

Povezanost rada

Strojarstvo, Temeljne tehničke znanosti

Poveznice