Multi-objective robust design optimization of a sewing mechanism under uncertainties

Bilel Najlawi (), Mohamed Nejlaoui, Zouhaier Affi and Lotfi Romdhane
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Bilel Najlawi: University of Monastir
Mohamed Nejlaoui: University of Monastir
Zouhaier Affi: University of Monastir
Lotfi Romdhane: American University of Sharjah

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 2, No 21, 783-794

Abstract: Abstract This work deals with the multi-objective robust design optimization of a needle-bar-and-thread-take-up-lever (NBTTL) mechanism used in sewing machines. A combined multi-objective imperialist competitive algorithm and Monte Carlo method are developed and used for the robust multi-objective optimization of the NBTTL mechanism. This robust optimization considers simultaneously the Needle Jerk, the transmission angle, the coupler tracking error and their standard deviations where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the NBTTL performances to the design parameters uncertainties compared to the deterministic one and to the commercialized Juki 8700 machine.

Keywords: Robust design; Sewing machine; Uncertainty; Monte Carlo; MOICA (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-016-1284-0

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