STOCK ANALYSIS OF THE PRODUCTION PROCESS USING FUZZY INFERENCE FOR DECISION MAKING: CASE STUDY
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Tipo do ITEM
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Artigo Ciêntifico
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Título do Artigo
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STOCK ANALYSIS OF THE PRODUCTION PROCESS USING FUZZY INFERENCE FOR DECISION MAKING: CASE STUDY
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Descrição
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The objective of the work is to propose a methodology for stock assessment and decision making
in a phyto cosmetics company, using fuzzy logic. In this case study, we tried to answer the level
of production and, consequently, the reasonableness of the stock. Such AI technique was chosen
because it is the most suitable for better decision making. With the results obtained by the
simulation with the real data, it was possible to verify that using the fuzzy logic technique the
decision making had a greater precision for the applied scenario and this will bring benefits to the
company, as well as the minimization of storage costs and weekly production beyond what is
necessary. It is concluded that the methodology was able to achieve the established objectives,
indicating by means of fuzzy logic a better decision making in the production of products.
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Abstract
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The objective of the work is to propose a methodology for stock assessment and decision making
in a phyto cosmetics company, using fuzzy logic. In this case study, we tried to answer the level
of production and, consequently, the reasonableness of the stock. Such AI technique was chosen
because it is the most suitable for better decision making. With the results obtained by the
simulation with the real data, it was possible to verify that using the fuzzy logic technique the
decision making had a greater precision for the applied scenario and this will bring benefits to the
company, as well as the minimization of storage costs and weekly production beyond what is
necessary. It is concluded that the methodology was able to achieve the established objectives,
indicating by means of fuzzy logic a better decision making in the production of products.
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Língua do arquivo
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inglês
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Data da Publicação
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Ano 2021
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Palavra-chave
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Inventory Control
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Fuzzy Logic
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Process Control
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Decision Making
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Autores
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Pablo Rock Dias Carvalho
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Rui Nelson Otoni Magno
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Ricardo Silva Parente
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Jandecy Cabral Leite
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Local
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ITEGAM - Manaus, 2021
