Optimized production and inventory decisions for a mixed make-to-order/make-to-stock ready-made garment manufacturer

In this thesis, a production and inventory planning model for mixed make-to-order (MTO) make-to-stock (MTS) production system in garment industry. Where the dominant production is typically for the Make-to-order production and the make-to-stock production is penetrating the mainstream production (MTO) as a way of enhancing the revenues and maintaining a positive cash flow, that are often degraded due to either seasonality of demands or production planning challenges. The model considers capacity planning for the mixed environment when there are predictable fluctuating demands. Due to the nature of the clothing business, it is challenging for a garment manufacturer to cope with seasonal changes while having the best capacity utilization. The literature acknowledges production planning in the garment industry. While a little focus was for capacity planning for seasonal fluctuating demands. Mathematical programming for capacity planning in a mixed MTO and MTS garment-manufacturing environment is a viable approach that can provide effective management decisions that can help the garment industry to strive in today’s competitive pace. The proposed model considers distributing the available capacity between MTO and MTS production and the implications of the costs and revenues for different capacity distribution. Decisions made on the production amounts, inventory levels and generated revenues are attained. The model was verified and validated by applying it to a local ready- made garment factory. The results ensured the validity of the proposed model. When analysis was made to the parameters that influence the decisions, it was found that distributing the capacity between MTO and MTS with different percentages had significant impact on the revenues and costs. The model was very sensitive to the increases in the fabric price and subcontracting costs while the overall net profits were not significantly affected by the changes in the inventory holding cost. Last, this work is useful in helping garment manufacturers adapt rapidly to seasonal changes by deploying their capacity effectively in favor of their projected seasonal plans

Sistema de apoio à decisão para a melhoria da produção numa empresa industrial

Atualmente, um dos recursos mais importantes para o sucesso de uma empresa é informação. A capacidade de recolha e processamento de dados para auxiliar a tomada de decisões, seja no mercado a apostar ou no equipamento a investir, permite otimizar processos envolvidos em áreas de produção, controlo de qualidade, distribuição, venda, etc. resultando numa diminuição de custos associados a desperdícios de materiais, tempo, consumíveis, reparações, etc. O presente estudo pretende demonstrar a importância da utilização de sistemas de apoio à tomada de decisão, em particular no setor industrial, bem como do conceito da indústria 4.0. Este trabalho foi realizado, no âmbito de um estágio curricular, na empresa Amorim Revestimentos S.A., e teve como objetivo principal o desenvolvimento de uma ferramenta, denominada ARSimTool, para a execução de simulações da ocupação das linhas de produção, após ser fornecido uma lista de fluxos de artigos de pavimento e decorativos de paredes, composto por cortiça. Esta foi requisitada em alternativa ao sistema existente, oferecendo capacidades de imitação do modelo produtivo real mais avançadas e funcionalidades adicionais como uma interface intuitiva, automação de atualização de dados, criação de cenários de teste, gestão e edição de fluxos de produção, entre outros.One of the most valued resources for a company's success nowadays is information. The ability to collect and process data to assist in decision making, whether in the market section or equipment to invest in, provides the means to improve processes involving production, quality control, distribution, sales, etc. resulting in reduced costs associated with waste regarding materials, time, consumables, repairs, etc. This research aims to demonstrate the importance of decision support systems and simulation tools in process optimization, focusing on the industrial sector, and the implementation of the industry 4.0 concept. Simultaneously, within a curricular internship in the company Amorim Revestimentos S.A., a tool, named ARSimTool, was developed to perform the simulation of occupational levels of production lines, after providing a list of flooring and wall covers assembly routes, composed of cork. This was requested as an alternative to the existing method, offering advanced representation capabilities of the real model and additional functionality on interface accessibility, autonomous data recovering, creation of testing scenarios, management of product routes along the production floor, among others

Metodologias de planeamento e gestão da produção na indústria metalúrgica

Mestrado em Engenharia e Gestão IndustrialO presente trabalho propõe demonstrar como o sistema PHC Manufactor se adequa à empresa em estudo, Ciclo Fapril, apresentando as opções de planeamento que este oferece, as dificuldades com que a empresa se irá deparar e, quando possível, o que fazer para ultrapassar as adversidades colocadas pelo sistema. Numa segunda parte são estudadas algumas heurísticas, nomeadamente FIFO, Tempo de Processamento, EDD, MOR e LOR, para se perceber qual a que melhor se adapta à empresa, de forma a poder cumprir com os prazos acordados. Posteriormente utilizou-se a heurística com melhores resultados e fez-se algumas alterações aos tempos de processamento dos centros de trabalho para melhorar a sua capacidade de resposta aos pedidos. No Final deste estudo percebeuse que o planeamento por EDD era o que melhor se adaptava a empresa. Percebeu-se ainda que os centros de trabalho AS e AT são os que têm menor produtividade e por este motivo se deveria aumentar a sua produtividade, de forma a aumentar a produtividade global.The present work intends to demonstrate how the PHC Manufactor system is adapted to the company in study, Ciclo Fabril. Showing the planning options it offers, the difficulties that the company will come across and what to do to overcome those adversities. In the second part of this work will be study some heuristic, namely FIFO, Processing time, EDD, MOR and LOR, to understand which one is the best suitable to accomplish the agreements made by the company. The heuristic with best results was found and were made a few adjustments to the production time of the machine to decrease time and improve the response that was agreed. In the end of this study was perceptible that the company should use the EDD plan, and was also visible that the AS and AT machines were the least productive and for that reason it should be increased, then the global production will increase as well