T
Tatjana V. Sibalija
Researcher at Metropolitan University
Publications - 38
Citations - 576
Tatjana V. Sibalija is an academic researcher from Metropolitan University. The author has contributed to research in topics: Taguchi methods & Particle swarm optimization. The author has an hindex of 12, co-authored 35 publications receiving 449 citations. Previous affiliations of Tatjana V. Sibalija include European University & University of Belgrade.
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Particle swarm optimisation in designing parameters of manufacturing processes: A review (2008–2018)
TL;DR: An analysis of the particle swarm optimisation (PSO) implementation in designing parameters of heterogeneous manufacturing processes, both conventional and emerging, new processes is presented and could serve as a basis for the future research and implementation directions.
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An integrated approach to optimise parameter design of multi-response processes based on Taguchi method and artificial intelligence
TL;DR: An integrated model for experimental design of processes with multiple correlated responses is proposed, composed of three stages which use Taguchi’s quality loss function to present relative significance of responses and multivariate statistical methods to uncorrelate and synthesise responses into a single performance measure.
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Multi-response design of Nd:YAG laser drilling of Ni-based superalloy sheets using Taguchi’s quality loss function, multivariate statistical methods and artificial intelligence
Tatjana V. Sibalija,Sanja Petronić,Vidosav D. Majstorovic,Radica Prokić-Cvetković,Andjelka Milosavljevic +4 more
TL;DR: In this paper, a hybrid design strategy for the determination of the optimum laser drilling parameters which simultaneously meets the requirements for seven quality characteristics (responses) of the holes produced during pulsed Nd:YAG laser drilling of a thin sheet of nickel-based superalloy Nimonic 263.
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Towards an intelligent approach for CMM inspection planning of prismatic parts
TL;DR: In this paper, the authors present a model of prismatic parts inspection planning on CMMs, in terms of an intelligent concept of inspection planning, composed of inspection feature construction, sampling strategy, probe accessibility analysis, automated collision-free generation, and probe path planning.
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An intelligent approach to robust multi-response process design
TL;DR: In this article, an integrative, general and intelligent approach to the multi-response process design, based on Taguchi's method, multivariate statistical methods and artificial intelligence techniques, is presented.