SIMULAÇÃO DO PROCESSO DE PRODUÇÃO DE UMA INDÚSTRIA DE ÁGUA MINERAL PELO MÉTODO SYSTEM DYNAMICS

• Ano de defesa: 2010
• Autor(a) principal: SILVA, Giselle de Lima Paixão e
• Orientador(a): GERALDINE, Robson Maia
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Goiás
• Programa de Pós-Graduação: Mestrado em Ciência e Tecnologia de Alimentos
• Departamento: Ciencias Agrárias - Agronomia
• País: BR
• Palavras-chave em Português: 1. Águas minerais - Indústria - Simulação por computador; 2. Águas minerais-Indústria; 1. Água mineral; 2. Simulação; 3. Modelo computacional; 4. Sistema; 5. Indústria
• Palavras-chave em Inglês: 1. Mineral Water; 2. Simulation; 3. Computational model; 4. System; 5. Industry
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::CIENCIA E TECNOLOGIA DE ALIMENTOS::TECNOLOGIA DE ALIMENTOS
• Link de acesso: http://repositorio.bc.ufg.br/tede/handle/tde/1458

The processing of mineral water is characterized by a system composed of step sequences, input variables, parameters and output variables. Thus, this work was conducted with the objective of implementing a computer model to simulate the steps that comprise the operational flowchart of a mineral water industry, using the software Stella 8.0. The model defined as dynamic, stochastic and discrete consisted of eleven interconnected blocks. It was built following the steps of characterizing the real system, creating the conceptual model, structuring and verification of computational model, data collection, and model validation. From data collected in the real system we obtained fits of the distributions used in assembling and verifying the model with the help of the @ risk 5.5 program. Validation of the program was conducted by comparing the data (number of bottles to be processed and total processing time) of the real system with simulated data, using regression analysis and the program Statistic 6.0 (Statsoft). The values collected in the real system were within the upper and lower limits on the graph obtained by regression analysis, with a confidence level of 95%, ensuring that the computer model adequately represents the real system. Fails in the process were identified by analyzing of collected values needed more processing time than the simulated values, for the same amount of bottles. However, the computational model developed is appliable to simulate the dynamics of processing lines of Mineral Water, being a tool of production control, which allows the visualization of the behavior of the real system, facilitates the identification of errors, improve production flow, and reduces manufacturing costs by controlling the total processing time.