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Abstract(s)
Atualmente, os sistemas de produção necessitam de lidar com ambientes produtivos cada vez mais complexos e dinâmicos. A progressiva evolução de fatores como o mercado, o produto, a tecnologia e o processo produtivo representa um grande desafio para as indústrias e para os sistemas que gerem a produção. Lidar com estes desafios é crucial para a eficiência dos sistemas de produção. Porém, os sistemas tradicionais de controlo da produção, caracterizados por abordagens centralizadas de planeamento e controlo, não são flexíveis para lidar com perturbações no ambiente de produção, tornando os mesmos menos apropriados para lidar com o aumento da complexidade e dinâmica. A evolução permitiu o surgimento de novos sistemas, de controlo autónomo, denominados sistemas APC (Autonomous Production Control), caraterizados pela capacidade de os elementos do sistema interagirem entre si e processarem informação, tendo como objetivo a reação rápida e flexível às mudanças ou alterações que possam ocorrer nos sistemas de produção. Na dissertação aqui apresentada, são estudados três métodos de controlo autónomo de produção, QLE (Queue Lenght Estimator), PHE (Pheromones) e DWL (Direct Workload), em diferentes contextos produtivos. É introduzida uma decisão lançamento de trabalhos em produção e a decisão de despacho, testando o impacto das regras de sequenciação usadas a estes dois níveis de decisão. Os métodos usados foram avaliados usando a simulação discreta, com recurso ao software de simulação Arena, com o objetivo de perceber melhor o comportamento de cada um deles. Os resultados obtidos mostram um desempenho superior do método DWL no cenário base e o próprio método melhora o seu desempenho quando são testadas diferentes configurações do limite do nível de carga nas máquinas. No método DWL e QLE, a alteração das regras de sequenciação na pool e de despacho nas máquinas permite um comportamento idêntico do sistema. No método PHE e RANDOM, num limite não restritivo, a alteração das regras de despacho nas máquinas tem impacto, tendo uma performance superior com a regra FCFS.
Nowadays, production systems need to deal with increasingly complex and dynamic production environments. The progressive evolution of factors such as market, product, technology and production process represents a big challenge for the industries and production systems. Deal with these challenges is crucial to the efficiency of systems. However, traditional production control systems, characterized by centralized planning and control approaches, are not flexible to deal with disturbances in the production environment, making them less appropriate to cope with the increase in complexity and dynamics. The evolution allowed the creation of new systems, called APC (Autonomous Production Control) systens, characterized by the ability of the elements of the system to interact with each other and process information, aiming at the quick and flexible reaction to changes that occurs in production systems. In this project three methods for the independent control of production, QLE (Queue Length Estimator), PHE (Pheromones) and DWL (Direct Workload) are studied in different productive contexts. A decision to release the works in production is introduced and the dispatch decision, testing the impact of the sequencing rules used at these two decision levels. The methods used were evaluated using discrete simulation, using the ARENA simulation software, in order to understand the behavior of each one of them. The results show a superior performance of the DWL method in the base scenario and the method itself improves its performance when different configurations of the load level limit on the machines are tested. In the DWL and QLE method, changing the sequencing rules in the pool and in the machines allows identical behavior of the system. In the PHE and RANDOM, within a non-restrictive limit, changing the dispatching rules on the machines, has as impact, having a higher performance with FCFS rule.
Nowadays, production systems need to deal with increasingly complex and dynamic production environments. The progressive evolution of factors such as market, product, technology and production process represents a big challenge for the industries and production systems. Deal with these challenges is crucial to the efficiency of systems. However, traditional production control systems, characterized by centralized planning and control approaches, are not flexible to deal with disturbances in the production environment, making them less appropriate to cope with the increase in complexity and dynamics. The evolution allowed the creation of new systems, called APC (Autonomous Production Control) systens, characterized by the ability of the elements of the system to interact with each other and process information, aiming at the quick and flexible reaction to changes that occurs in production systems. In this project three methods for the independent control of production, QLE (Queue Length Estimator), PHE (Pheromones) and DWL (Direct Workload) are studied in different productive contexts. A decision to release the works in production is introduced and the dispatch decision, testing the impact of the sequencing rules used at these two decision levels. The methods used were evaluated using discrete simulation, using the ARENA simulation software, in order to understand the behavior of each one of them. The results show a superior performance of the DWL method in the base scenario and the method itself improves its performance when different configurations of the load level limit on the machines are tested. In the DWL and QLE method, changing the sequencing rules in the pool and in the machines allows identical behavior of the system. In the PHE and RANDOM, within a non-restrictive limit, changing the dispatching rules on the machines, has as impact, having a higher performance with FCFS rule.
Description
Keywords
Controlo Autónomo de Produção (APC) Simulação Planeamento de Produção Controlo Autonomous Production Control Simulation Production Planning Control