Open AccessLabour productivity in mixed-model manual assembly 4.0
Author(s) -
Adrian Miqueo,
Marshall A. Martin,
Marta Torralba,
J.A. Yagüe
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1193/1/012104
Subject(s) - productivity , assembly line , computer science , work (physics) , key (lock) , parametric statistics , manufacturing engineering , industrial engineering , operations research , engineering , economics , mathematics , statistics , mechanical engineering , computer security , macroeconomics
Manual assembly lines productivity is threatened by the increased complexity brought by mass customisation demand trends. Industry 4.0 offers potential solutions to address this situation, but the methodology to implement it is still a subject of study. As a preliminary step, this article aims to identify the dominant factors affecting the Key Performance Indicators of mixed-model assembly lines. To do so, parametric and discrete-events simulation models were developed, and Design of Experiments techniques were used. The results show that the key drivers for assembly line performance are number of work stations and batch size, and that increasing the work content ratio of the products assembled does not interact negatively with other factors. The results presented here pave the way for developing Industry 4.0 projects that address specifically the most relevant factors that affect assembly lines performance.