Estudo de desempenho do cluster tool abordagem baseada na teoria de controle supervisório

• Ano de defesa: 2018
• Autor(a) principal: Márcio Júnior Nunes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Teoria de controle supervisório; Sistemas de manufatura; Sistemas a eventos discretos; Cluster tool; Máximo paralelismo; Teoria do controle; Engenharia elétrica; Sistemas de tempo discreto
• Link de acesso: http://hdl.handle.net/1843/RAOA-BC2GFC

This work presents a study of the parameters that influence the cluster tool performance. Four different layouts are considered, two of the radial type, with 1 and 2 handler robots, and two of the linear type, with single input-output and separated input-output. To compare these layouts, the makespan and the Relative Accumulated Parallelism were used as performance metrics, the latter being an index proposed in this work. The values of theses metrics are obtained applying the Maximum Parallelism with Time Constraints algorithm to the supervisor responsible for the control of the plant, generated with the Supervisory Control Theory. This algorithm searches for the sequence with larger parallelism, considering the tasks execution times, and the result is the makespan and accumulated parallelism of this sequence. From the accumulated parallelism, the number of events to produce the wafer and the number of equipments in the considered layout was used to calculate the Relative Accumulated Parallelism. For each layout, the effect on these two metrics of the number of wafers, the processing time and the number of equipments in the layout was verified. The number of wafers was varied from 6 to 50, the processing times from 1 to 200 seconds and the number of chambers from 4 to 6. The analysis is performed comparing the makespan and the Relative Accumulated Parallelism in each layout, the makespan being a measure of quickness of the cluster tool, and the Relative Accumulated Parallelism being a measure of efficiency.