Priscila de Jesus Freitas Pinto, C. H. dos Santos Grecco, Carlos Alberto Nunes Cosenza
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Fuzzy Model for the Priorization Analysis of Variable Quality Performance: An Approach in Shipbuilding
The shipbuilding industry has evolved in recent years. Some quantitative and qualitative factors influence competitiveness of shipyards. The development of shipbuilding processes depends on evolution of manufacturing techniques, planning, organization and external environment. In general, regarding performance, quantitative variables are analyzed through mathematical and linear models. However, the qualitative variables, due to its subjectivity because it deals with human perceptions, it is not common for organizations to work on the performance of these factors. Then, this is the objective of the research, to analyze qualitative factors in shipbuilding in context with the Brazilian industry. The chosen that compose the proposed model are technology and industrial location. This research presents a prioritizing evaluation model of qualitative performance variables. So, presents as original the treatment by the fuzzy sets of qualitative critical factors expressed in linguistic terms by specialists working in the Brazilian sector, resulting in the prioritization of these factors. After result, the model was applied at specific shipyard. The results converge Brazil's real scenario and show that the proposed fuzzy model might be a good qualitative performance factor evaluation tool. Finally, to identify real the distance of a specific shipyard for to this research's model prioritization pattern by brazilian specialists.
期刊介绍:
Fuzzy Information and Engineering—An International Journal wants to provide a unified communication platform for researchers in a wide area of topics from pure and applied mathematics, computer science, engineering, and other related fields. While also accepting fundamental work, the journal focuses on applications. Research papers, short communications, and reviews are welcome. Technical topics within the scope include: (1) Fuzzy Information a. Fuzzy information theory and information systems b. Fuzzy clustering and classification c. Fuzzy information processing d. Hardware and software co-design e. Fuzzy computer f. Fuzzy database and data mining g. Fuzzy image processing and pattern recognition h. Fuzzy information granulation i. Knowledge acquisition and representation in fuzzy information (2) Fuzzy Sets and Systems a. Fuzzy sets b. Fuzzy analysis c. Fuzzy topology and fuzzy mapping d. Fuzzy equation e. Fuzzy programming and optimal f. Fuzzy probability and statistic g. Fuzzy logic and algebra h. General systems i. Fuzzy socioeconomic system j. Fuzzy decision support system k. Fuzzy expert system (3) Soft Computing a. Soft computing theory and foundation b. Nerve cell algorithms c. Genetic algorithms d. Fuzzy approximation algorithms e. Computing with words and Quantum computation (4) Fuzzy Engineering a. Fuzzy control b. Fuzzy system engineering c. Fuzzy knowledge engineering d. Fuzzy management engineering e. Fuzzy design f. Fuzzy industrial engineering g. Fuzzy system modeling (5) Fuzzy Operations Research [...] (6) Artificial Intelligence [...] (7) Others [...]