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Keywords = PROMETTHEE

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23 pages, 1576 KiB  
Article
Multi-Criteria Decision Making Methods for Selection of Lightweight Material for Railway Vehicles
by Varun Sharma, Fatima Zivic, Dragan Adamovic, Petar Ljusic, Nikola Kotorcevic, Vukasin Slavkovic and Nenad Grujovic
Materials 2023, 16(1), 368; https://doi.org/10.3390/ma16010368 - 30 Dec 2022
Cited by 21 | Viewed by 3382
Abstract
This paper deals with the selection of the optimal material for railway wagons, from among three different steel and three aluminium based materials, by using four different Multicriteria Decision Making Methods (MCDM) and comparing their ranking of the materials. We analysed: Dual-Phase 600 [...] Read more.
This paper deals with the selection of the optimal material for railway wagons, from among three different steel and three aluminium based materials, by using four different Multicriteria Decision Making Methods (MCDM) and comparing their ranking of the materials. We analysed: Dual-Phase 600 steel, Transformation-Induced Plasticity (TRIP) 700 steel, Twinning-Induced Plasticity (TWIP) steel, Aluminium (Al) alloys, Al 6005-T6, and Al 6082-T6, and porous Al structure with closed cells. Four different MCDM methods were used: VIKOR, TOPSIS, PROMETTHEE and the Weighted aggregated sum product assessment method (WASPAS). Key material properties that were used in the MCDM analysis were: density, yield strength (Y.S.), tensile strength (T.S.), Y.S./T.S. ratio, Youngs modulus (Y.M.), cost and corrosion resistance (C.R.). Research results indicate that aluminium and its alloys prove to be the most suitable material, based on setup criteria. Advanced steels also achieved good ranking, making them a valid option, immediately behind lightweight aluminium alloys. Porous aluminium did not perform well, according to the used MDCM methods, mainly due to the significantly lower strength exhibited by the porous structures in general. Full article
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28 pages, 6965 KiB  
Article
Optimizing Design of Smart Workplace through Multi-Objective Programming
by Shady Aly, Jan Tyrychtr and Ivan Vrana
Appl. Sci. 2021, 11(7), 3042; https://doi.org/10.3390/app11073042 - 29 Mar 2021
Cited by 4 | Viewed by 2604
Abstract
Smart environments have proven very supportive to the improvement of the performance of people in different workplaces. Plenty of applications have been introduced spanning different settings including healthcare, ambient assisted living, homes, offices, and manufacturing environment, etc. However, subjectivity and ambiguity prevail in [...] Read more.
Smart environments have proven very supportive to the improvement of the performance of people in different workplaces. Plenty of applications have been introduced spanning different settings including healthcare, ambient assisted living, homes, offices, and manufacturing environment, etc. However, subjectivity and ambiguity prevail in the majority of research, and still, up to date, rare approaches found quantitatively and objectively constructing or assessing the impact of smart enabling technologies on the performance of the subject environment. Further, no approaches have considered optimizing the adoption of those smart technologies with respect to objectives achievement. This article presents a novel optimization methodology for designing a smart workplace environment in conditions of ambiguity or fuzziness. The methodology begins with defining and weighing the overall goals and objectives of the workplace. The Prometthe multi-criterion decision-making technique is used to weigh the operational objectives with respect to the overall workplace goals. Next, the relation among basic building blocks of the model; namely: the operational objectives, smartness features, and smart enabling technologies are quantified, utilizing fuzzy relations. Then, the fuzzy goal programming techniques will be utilized to optimize the impact relation values while considering the budget constraint. The proposed optimization methodology is implemented on the development and optimization of the smart clinic, as a typical instance of the workplace. Full article
(This article belongs to the Special Issue Applications of Fuzzy Optimization)
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