Orientador: Prof. Dr. Douglas Alves Cassiano / Dissertação (mestrado) - Universidade Federal do ABC. Programa de Pós-Graduação em Energia, 2015. / O acionamento de equipamentos rotativos na indústria petroquímica pode ser realizado a partir de motores elétricos ou turbinas a vapor. Os motores elétricos consomem energia elétrica e as turbinas a vapor consomem combustíveis, como Gás Natural e o Óleo Combustível. Os custos com estes insumos sofrem influência de vários fatores: políticas públicas, valor do dólar, valor do preço de mercado (PLD), valores de contrato e a própria eficiência de cada equipamento. Dessa forma, o objetivo geral deste trabalho é identificar oportunidades de eficiência energética na gestão do acionamento de equipamentos rotativos típicos de uma Indústria Petroquímica brasileira. Diante de tantas influências que variam em um curto espaço de tempo, uma ferramenta de apoio a gestão é a modelagem de equações lineares e integrais mistas (Mixed Integer Linear Programming ¿ MILP) para tomada de decisão com múltiplos critérios em relação ao consumo de energia nestes equipamentos. Comprovou-se que utilizando MILP é possível conquistar ganhos de eficiência energética. A escolha ótima do tipo de acionamento dos equipamentos rotativos e demais graus de liberdade apresentaram ganho anual médio de R$ 1.679.000/ano. A modelagem com MILP se mostrou eficaz, acurada e robusta. Foi confirmada a importância de uma modelagem e simulação de resposta rápida e a sua execução numa frequência maior possível, uma vez que os ganhos potenciais executando-se o modelo uma vez por dia foram 81% maiores do executando-se uma vez por mês. Esta metodologia apresenta um potencial de aplicação em outras plantas industriais, desde que possuam características semelhantes à estudada. / Rotating equipments in petrochemical industry are usually driven using steam turbines or electric motors. Electric motors consume electricity and steam turbines consume fuels such as natural gas and fuel oil. The costs of these energy inputs are influenced by: public policy, dollar rate, market prices, contracts values and equipments efficiency. Thus, the aim of this study is to identify energy efficiency opportunities at rotating equipment drive management of a Brazilian Petrochemical Industry. With so many influences that range in a short time, a management support tool is Mixed Integer Linear Programming ¿ MILP for decision making with multiple criteria. It was possible to prove that using MILP can achieve energy efficiency gains. The optimal rotating equipment drive choice and other degrees of freedom had an average annual gain of R$ 1,679,000/year. MILP proved effective, accurate and robust. It confirmed the importance of modeling and simulation with quickly response and its implementation in a higher possible rate, since the potential gains running the model once per day were 81% higher performing once a month. This methodology has a potential application in other industrial plants, since they have similar characteristics to the studied.

Nowadays, by increasing competitions in business, decision-making in maintenance management gets higher priorities. While maintenance in many industries is known as a necessary evil, making cost-effective decisions constructed based on analytical and quantitative assessments improve maintenance position from a cost center into a profit generating one. Within the scope of rotating equipment maintenance, it is vital to consider both economic and technical variables integrated to survive in the competitive market. Taking the role of improving rotating equipment performance within a cost-effective approach into account, this project proposes a consistent model followed by substantial results. The model application can be briefed in improvement of decision-making processes from technical and economic perspectives to direct them into the company profitability aligned with the company goals. Further, it proposes technical and economic indicators and improves utilization of maintenance resources including personnel skills and experience to enhance maintenance performance and develop cost-effective scenarios. Within the model, eMDSS (software) is used as an intelligent facilitator/tool which improves accurate decision-making and identifying and prioritizing maintenance problems. To ensure from the model and its tool applicability, it is applied on a real case study and reliability of the achieved results are tested and approved in detail. In result, the project is successful in evaluating previous technical and economic decisions and selecting the most cost-effective scenario for future with a saving value exceeding 133K€ and profit of 114K€ for the case equipment.