The use of discrete simulation models to analyse production environments: a case study

Simulation tools are becoming increasingly powerful for the optimisation of manufacturing processes. The study described in this dissertation was held on a Portuguese company that produces a diverse range of breads and the main objective of this study was to analyse and propose improvements for diff...

ver descrição completa

Detalhes bibliográficos
Autor principal: Setti, Fabiane Kupchak (author)
Formato: masterThesis
Idioma:eng
Publicado em: 2019
Assuntos:
Texto completo:http://hdl.handle.net/10198/19764
País:Portugal
Oai:oai:bibliotecadigital.ipb.pt:10198/19764
Descrição
Resumo:Simulation tools are becoming increasingly powerful for the optimisation of manufacturing processes. The study described in this dissertation was held on a Portuguese company that produces a diverse range of breads and the main objective of this study was to analyse and propose improvements for different productive processes of the company, through the use of discrete event simulation. During the study, it was conducted a bibliographical research on the simulation and its applications in manufacturing processes. Subsequently, it was performed a data collection of relevant information needed for the creation of models and in this context, four processes have been chosen (wheat bread, rye bread, fig bread and “bijou” bread) to be modelled using the Simulation Modelling based on Intelligent Objects software (Simio R ). After the analysis of the models results that represent the company’s current reality, it was identified the need for improvements and so different scenarios were created with this purpose. Among the results obtained, it is possible to highlight suggestions for improvement that caused the daily batch of products to be totally produced in a working shift, which was not possible before. A standardisation model of the fig bread process was also created, as well as the creation of different scenarios of mixed production, thus finding the maximisation of the combined production of products. All the results can be applied in the reality of the company to increase production, since they do not involve the purchase of new equipment.